A pesquisa se trata de um estudo de caso com objetivo de apresentar e discutir a ferramenta de monitoria centralizada em pesquisa clínica, aplicada a um estudo clínico conduzido na Plataforma de Pesquisa Clínica VPPCB/Fiocruz e compartilhar o código do software R utilizado para construção da ferramenta. Essa ferramenta de monitoramento centralizado analisa a qualidade dos dados clínicos eletrônicos para identificar desvios de protocolo, sinais de alerta de farmacovigilância, métricas de desempenho do estudo e integridade dos dados por meio de avaliações automatizadas remotamente. Usando um script R para garantir a reprodutibilidade dessas avaliações de qualidade de dados, essa ferramenta pode aumentar a segurança do paciente, pois o controle dos EAs é aprimorado; acelerar a limpeza dos dados antes das análises estatísticas; avaliar as métricas de desempenho dos locais de estudo; e diminuir o número de visitas de monitoramento no local, impactando nos custos, prazos e segurança dos estudos clínicos (pt) The research is a case study with the objective of presenting and discussing the monitoring tool centered on clinical research, applied to a clinical study conducted on the Clinical Research Platform VPPCB/Fiocruz and sharing the R software code used to build the tool. This centralized monitoring tool analyzes the quality of electronic clinical data to identify protocol deviations, pharmacovigilance red flags, study performance metrics and data integrity through remotely automated assessments. Using an R script to ensure the reproducibility of these data quality assessments, this tool can increase patient safety as the control of AEs is improved; speed up data cleaning before statistical analysis; evaluate the performance metrics of the study sites; and decrease the number of on-site monitoring visits, impacting the costs, timing and safety of clinical trials (en) La investigación es un estudio de caso con el objetivo de presentar y discutir la herramienta de monitoreo centrada en la investigación clínica, aplicada a un estudio clínico realizado en la Plataforma de Investigación Clínica VPPCB/Fiocruz y compartir el código del software R utilizado para construir la herramienta. Esta herramienta de monitoreo centralizado analiza la calidad de los datos clínicos electrónicos para identificar las desviaciones del protocolo, las señales de alerta de farmacovigilancia, las métricas de rendimiento del estudio y la integridad de los datos a través de evaluaciones automatizadas de forma remota. Usando un script R para garantizar la reproducibilidad de estas evaluaciones de calidad de datos, esta herramienta puede aumentar la seguridad del paciente a medida que se mejora el control de los EA; acelerar la limpieza de datos antes del análisis estadístico; evaluar las métricas de desempeño de los sitios de estudio; y disminuir el número de visitas de control in situ, lo que repercutirá en los costos, el tiempo y la seguridad de los ensayos clínicos.La investigación es un estudio de caso con el objetivo de presentar y discutir la herramienta de monitoreo centrada en la investigación clínica, aplicada a un estudio clínico realizado en la Plataforma de Investigación Clínica VPPCB/Fiocruz y compartir el código del software R utilizado para construir la herramienta. Esta herramienta de monitoreo centralizado analiza la calidad de los datos clínicos electrónicos para identificar las desviaciones del protocolo, las señales de alerta de farmacovigilancia, las métricas de rendimiento del estudio y la integridad de los datos a través de evaluaciones automatizadas de forma remota. Usando un script R para garantizar la reproducibilidad de estas evaluaciones de calidad de datos, esta herramienta puede aumentar la seguridad del paciente a medida que se mejora el control de los EA; acelerar la limpieza de datos antes del análisis estadístico; evaluar las métricas de desempeño de los sitios de estudio; y disminuir el número de visitas de control in situ, lo que repercutirá en los costos, el tiempo y la seguridad de los ensayos clínicos (es)

The Digital Centralized Patient Monitoring System (DCPMS) market is experiencing significant growth as healthcare providers increasingly recognize the benefits of real-time patient data and remote monitoring solutions. DCPMS encompasses various technologies that enable healthcare professionals to observe and analyze

The Medical Central Monitoring System for Cardiac Rehabilitation Remote Monitoring market has emerged as a pivotal segment in the healthcare industry, revolutionizing the way cardiac patients are monitored and rehabilitated from the comfort of their homes. These advanced systems integrate cutting-edge technology to

The Obstetric Central Monitoring System (OCMS) market is experiencing significant growth as healthcare facilities increasingly recognize the importance of optimized maternal and fetal monitoring during pregnancy and labor. This sophisticated system allows for real-time tracking of vital signs and well-being of both

Statistical Monitoring of The Green Deal. Data available through MRA legislation

Abstract

The Food and Agriculture Organization of the United Nations (FAO) has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). FAO conducted the third round of the DIEM-Monitoring among households to assess agricultural livelihoods and food security in the Central African Republic between 6 September and 6 October 2022. Data were collected through telephone surveys in 17 prefectures: Bangui, Bamingui Bangoran, Basse Kotto, Haute Kotto, Haut Mbomou, Kémo, Lobaye, Mambéré Kadeï, Mbomou, Nana Manbéré, Nana-Gribizi, OMbella M'Poko, Ouaka, Ouham, Ouham-Pendé, Sangha Mbaéré and Vakaga. A total of 1 985 households were interviewed. Data collection took place during the rainy season. For more information, see https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

Data were collected through telephone surveys in 17 prefectures: Bangui, Bamingui Bangoran, Basse Kotto, Haute Kotto, Haut Mbomou, Kémo, Lobaye, Mambéré Kadeï, Mbomou, Nana Manbéré, Nana-Gribizi, OMbella M'Poko, Ouaka, Ouham, Ouham-Pendé, Sangha Mbaéré and Vakaga. A total of 1 985 households were interviewed. Data collection took place during the rainy season.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergency and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

STATISTICAL DISCLOSURE CONTROL (SDC) The dataset was anonymized using Statistical Disclosure methods by the Data in Emergencies Hub team and reviewed by the Office of Chief Statistician of FAO. All direct identifiers have been removed prior to data submission.

Original source here.

This dataset was collected in the Cranfield Multiphase Flow Facility aiming to serve as a benchmark case for statistic process monitoring.

Read this paper for more information.

Cite as:

Yi Cao (2020). A Benchmark Case for Statistical Process Monitoring - Cranfield Multiphase Flow Facility (https://www.mathworks.com/matlabcentral/fileexchange/50938-a-benchmark-case-for-statistical-process-monitoring-cranfield-multiphase-flow-facility), MATLAB Central File Exchange. Retrieved November 23, 2020.

License:

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• Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The Bedside Monitors and Centralized Monitor market is experiencing significant growth as healthcare facilities increasingly prioritize patient safety and continuous monitoring. These medical devices play a crucial role in monitoring patients' vital signs, such as heart rate, blood pressure, oxygen saturation, and r

The decline in escapement monitoring effort and the importance of these data for annual assessment of stock status prompted this review of the escapement indicator streams and the discussions regarding survey priorities, methods, and costs with the groups that have been conducting these escapement surveys in recent years. These discussions included representatives from Fisheries and Oceans Canada (DFO), Charter Patrol (CP) operators and most of the NCC First Nations. Each individual or group was provided with an Excel file that contained all the available escapement estimates and metadata for each NCC stream and identified those streams that were previously classified as “indicator streams” for each species. Individuals were asked to identify any indicator streams that should be removed from the list priority streams to monitor each year and streams that should be added to the list to fill monitoring gaps, improve coverage of a statistical area or CU, or provide more reliable escapement estimates than one or more of the current indicator streams. This report provides a series of tables which summarize of our findings by monitoring method for each Statistical Area, monitoring group, species, and CU. Recommendations are provided regarding how to ensure the annual surveys of indicator streams are conducted in a consistent and sustainable manner.

The Hospital Central Monitoring System (HCMS) market plays a pivotal role in modern healthcare, providing an integrated platform for the continuous monitoring of patients' vital signs within clinical settings. These systems are essential for enhancing patient safety, streamlining workflow, and improving clinical out

Abstract

The Government of Iraq, with support from UNICEF finalized and launched a Multiple Indicator Cluster Survey (MICS 6) in 2018. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. Data and information from MICS6 provides credible and reliable evidence for the Government of Iraq to monitor the National Development Plan and establish baselines and monitor progress towards Sustainable Development Goals (SGDs). It helps the government and its stakeholders to understand disparities and the wider development challenges in the country.

The 2018 Iraq MICS has as its primary objectives:

• To provide high quality data for assessing the situation of children, adolescents, women and households in Iraq;

• To furnish data needed for monitoring progress towards national goals, as a basis for future action;

• To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable;

• To validate data from other sources and the results of focused interventions;

• To generate data on national and global SDG indicators;

• To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention.

Geographic coverage

The sample for the Iraq MICS 2018 was designed to provide estimates at the national, regional and governorates level, for urban and rural areas. Specifically the sample for the Iraq MICS 2018 survey includes 2 regions - Kurdistan and South/Central Iraq and 18 governorates - Duhok, Nainawa, Sulaimaniya, Kirkuk, Erbil, Diala, Anbar, Baghdad, Babil, Karbalah, Wasit, Salahaddin, Najaf, Qadissiyah, Muthana, Thiqar, Musan, and Basra.

Analysis unit

• Individuals

• Households

Universe

The MICS survey considers the households and their members in all urban and rural areas of Iraq as the Universe. Thus, the Universe for Iraq consists of all persons in the country residing in various geographic locations considering all special ethnic or economic groups in the rural and urban areas of Iraq. For the purposes of this survey, Internally Displaced Persons living in United Nations/government notified camps, military installations, and non-residential units such as business establishments were not considered in the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING FRAME

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The last census in Iraq was carried out in 1998 and the sampling frame was developed during that time. The most recent update of this sampling frame was done in 2009 which was used by Central Statistical Office (CSO) for the selection of the Clusters in Iraq region. On the other hand, the Kurdistan Region Statistical Office (KRSO) has updated the 2009 sampling frame for the 3 main cities of Kurdish region and their periphery and used it to draw the Clusters. The primary sampling units (PSUs) selected at the first stage were the enumeration areas (EAs). A listing of households was conducted in each sample EA, and a sample of households was selected at the second stage.

SAMPLE SIZE AND SAMPLE ALLOCATION

The sample size has been calculated using the prevalence rates of key indicators from the 2011 MICS. For the purpose of identifying the optimal sample size for 2018 MICS, all the factors such as time, cost, domain of estimation, sampling and non-sampling errors were taken into account, as well as the desired level of precision of the key prevalence indicator. The sample size was calculated at the governorate level. It was decided that 2018 MICS will provide the estimates at the governorate level, so the indicative sample size has been calculated using governorate as the domain for the geographic representation. The formula for calculating the sample size is described in Appendix A of report available in related materials.

A number of meetings were held in the CSO to finalize the sample size, and various refinements were studied using the referred formula. As a result of these discussions the MICS Technical Committee reached a consensus on a sample size of 1,080 households for each governorate of Iraq, where each governorate was divided into 90 sample clusters and 12 households were selected per cluster (90 clusters x 12 households = 1,080 households). Baghdad was sub-divided into two administrative areas, therefore 19 total individual domains were used for a total sample size of 20,520 households (19 domains x 1,080 households).

One-third of the sampled households was selected for water quality testing, which means 360 households per governorate or 6,840 (360 X 19) households for the overall survey. The subsample of 4 households for the water quality testing in each cluster are selected using systematic random sampling.

Each Governorate is further stratified into urban and rural areas, and the sample within each governorate is allocated proportionately to the urban and rural strata based on the population. The urban and rural areas within each governorate are the main sampling strata. Within each stratum, a specified number of clusters is selected systematically using probability proportionate to size (PPS) sampling methodology. After the selection of the clusters in each rural and urban stratum, a new listing of households was conducted in each sample cluster. Then a systematic random sample of 12 households per cluster is drawn from the listing for each rural and urban sample cluster.

SELECTION OF ENUMERATION AREAS (CLUSTERS):

Census enumeration areas were selected from each of the sampling strata by using systematic probability proportional to size (pps) sampling procedures, based on the number of households in each enumeration area from the Iraq 2009 sampling frame. The first stage of sampling was thus completed by selecting the required number of sample EAs (specified in Table SD.2) from each of the 19 sampling domains, separately for the urban and rural strata. However, there are a few areas belonging to two governorates that were not accessed due to security reasons. These governorates are Nainawa and Kirkuk. In Nainawa 5 districts were excluded (Ba'aj, Al-Hadar, Telafer, Sinjar and Makhmoor), while only Haweja district in Kirkuk was excluded. The excluded districts represent around 22% of the urban population and 51% of the rural population in Nainawa. The percentage of not accessed area in final sample for Kirkuk represents 5% of the Urban and 42% of the rural population, following the exclusion of Haweja district.

SELECTION OF HOUSEHOLDS:

Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to Mhi (the total number of households in each enumeration area) at the Central Statistical Office, where the selection of 12 households in each enumeration area was carried out using random systematic selection procedures. The MICS6 spreadsheet template for systematic random selection of households was adapted for this purpose.

The Iraq 2018 MICS also included water quality testing for a subsample of households within each sample cluster. A subsample of 4 of the 12 selected households was selected in each sample cluster using random systematic sampling for conducting water quality testing, for both water in the household and at the source, including a chlorine test. The MICS6 household selection template includes an option to specify the number of households to be selected for the water quality testing, and the spreadsheet automatically selected the corresponding subsample of households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a water quality testing questionnaire administered in 4 households in each cluster of the sample; 3) a questionnaire for individual women administered in each household to all women age 15-49 years; 4) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and 5) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

The questionnaires were based on the MICS6 standard questionnaires. From the MICS6 model Arabic version, the questionnaires were customised and translated to two Kurdish dialects and were pre-tested in 3 governorates (Baghdad, Najaf and Basra) in South/Central Iraq region and 3 governorates (Duhok, Erbil & Sulaimaniya) in Kurdistan region of Iraq during Dec 2017/Jan 2018. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

Cleaning operations

Data were received at the Central Statistical Organization (CSO) via Internet File Streaming System (IFSS), integrated into the management application on the supervisors' tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.

During data collection and following the completion of fieldwork, data were edited according to editing process described in details in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.

Data

Abstract

The general objective of CSA's Agricultural Sample Survey (AgSS) is to collect basic quantitative information on the country's agriculture that is essential for planning, policy formulation, monitoring and evaluation of mainly food security and other agricultural activities. The AgSS is composed of four components: Crop Production Forecast Survey, Meher Season Post Harvest Survey (Area and production, land use, farm management and crop utilization), Livestock Survey and Belg Season Survey.

The specific objectives of Meher Season Post Harvest Survey are to estimate the total crop area, volume of crop production and yield of crops for Meher Season agriculture in Ethiopia.

Geographic coverage

The annual Agricultural Sample Survey (Meher season) covered the entire rural parts of the country except the non-sedentary population of three zones of Afar and six zones of Somali regions

Analysis unit

Agricultural household/ Holder/ Crop

Universe

The survey covered agricultural households in the sample selected regions.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame The list containing EAs of all regions and their respective households obtained from the 2007 (1999 E.C) cartographic census frame was used as the sampling frame in order to select the primary sampling units (EAs). Consequently, all sample EAs were selected from this frame based on the design proposed for the survey. The second stage sampling units, households, were selected from a fresh list of households that were prepared for each EA at the beginning of the survey.

Sample Design In order to select the sample a stratified two-stage cluster sample design was implemented. Enumeration areas (EAs) were taken to be the primary sampling units (PSUs) and the secondary sampling units (SSUs) were agricultural households. The sample size for the 2010/11 agricultural sample survey was determined by taking into account of both the required level of precision for the most important estimates within each domain and the amount of resources allocated to the survey. In order to reduce non-sampling errors, manageability of the survey in terms of quality and operational control was also considered.

All regions were taken to be the domain of estimation for which major findings of the survey are reported.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2011-2012 annual Agricultural Sample Survey used structured questionnaires to collect agricultural information from selected sample households. List of forms in the questionnaires: - AgSS Form 2004/0: It contains forms that used to list all households in the sample areas. - AgSS Form 2004/1: It contains forms that used to list selected agricultural households and holders in the sample areas. - AgSS Form 2004/2A: It contains forms that used to collect information about crops, results of area measurements covered by crops and other land uses. - AgSS Form 2004/2B: It contains forms that used to collect information about miscellaneous questions for the holders. - AgSS Form 2004/4: It contains forms that used to collect information about list of temporary crop fields for selecting crop cutting plots. - AgSS Form 2004/5: It contains forms that used to collect information about list of temporary crop cutting results.

Cleaning operations

Editing, Coding and Verification Statistical data editing plays an important role in ensuring the quality of the collected survey data. It minimizes the effects of errors introduced while collecting data in the field, hence the need for data editing, coding and verification. Although coding and editing are done by the enumerators and supervisors in the field, respectively, verification of this task is done at the Head Office.

An editing, coding and verification instruction manual was prepared and reproduced for this purpose. Then 66 editors-coders and verifiers were trained for two days in editing, coding and verification using the aforementioned manual as a reference and teaching aid. The completed questionnaires were edited, coded and later verified on a 100 % basis before the questionnaires were passed over to the data entry unit. The editing, coding and verification exercise of all questionnaires took 18 days.

Data Entry, Cleaning and Tabulation Before data entry, the Agriculture, Natural Resources and Environment Statistics Directorate of the CSA prepared edit specification for the survey for use on personal computers for data consistency checking purposes. The data on the edited and coded questionnaires were then entered into personal computers. The data were then checked and cleaned using the edit specifications prepared earlier for this purpose. The data entry operation involved about 70 data encoders, 10 data encoder supervisors, 12 data cleaning operators and 55 personal computers. The data entered into the computers using the entry module of the CSPRO (Census and Survey Processing System) software, which is a software package developed by the United States Bureau of the Census. Following the data entry operations, the data was further reviewed for data inconsistencies, missing data … etc. by the regular professional staff from Agriculture, Natural Resources and Environment Statistics Directorate. The final stage of the data processing was to summarizing the cleaned data and produce statistical tables that present the results of the survey using the tabulation component of the PC based CSPRO software produced by professional staff from Agriculture, Natural Resources and Environment Statistics Directorate.

Response rate

A total of 2,290 Enumeration Areas (EAs) were selected. However, due to various reasons that are beyond control, in 17 EAs the survey could not be successful and hence interrupted. Thus, all in all the survey succeeded to cover 2,273 EAs (99.25 %) throughout the regions. The Annual Agricultural Sample survey (Meher season) was conducted on the basis of 20 agricultural households selected from each EA. Regarding the ultimate sampling units, it was intended to cover aa total of 47,080 gricultural households, however, 45,575 (98.9 %) were actually covered by the survey.

Sampling error estimates

Estimation procedure of totals, ratios, sampling error and the measurement of precision of estimates (CV) are given in Appendix-I and II of the final report. Distribution of sampling units (sampled and covered EAs and households) by stratum is also presented in Appendix-III of the final report.

Abstract

The Food and Agriculture Organization of the United Nations (FAO) has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality).

Data were collected through computer-assisted telephone interviews in 11 provinces (Ituri, Kasai, Kasai-Central, Kasai-Oriental, Kwango, North Kivu, North Ubangi, South Kivu, South Ubangi, Tanganyika and Tshopo) out of 26. The sample of 2 716 agricultural and non-agricultural households was selected at random, following a stratified simple random sampling design that has minimal design effect.

For more information, see https://data-in emergencies.fao.org/pages/monitoring.

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

Data were collected through computer-assisted telephone interviews in 11 provinces (Ituri, Kasai, Kasai-Central, Kasai-Oriental, Kwango, North Kivu, North Ubangi, South Kivu, South Ubangi, Tanganyika and Tshopo) out of 26. The sample of 2 716 agricultural and non-agricultural households was selected randomly, following a stratified simple random sampling design that has minimal design effect.

Surveys are designed based on country-specific needs, objectives, and constraints. They aim to achieve a 10 percent margin of error, a 95 percent confidence level, administrative-level granularity, and sufficient sample sizes for key target populations, including agricultural households.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the Data in Emergencies Hub at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

STATISTICAL DISCLOSURE CONTROL (SDC) The dataset was anonymized using Statistical Disclosure methods by the Data in Emergencies Hub and reviewed by the Statistics Division of FAO. All direct identifiers have been removed prior to data submission.

Abstract

The Trinidad and Tobago Multiple Indicator Cluster Survey (MICS) was conducted from November to December 2011 by the Ministry of Social Development and Family Services and Central Statistical Office in collaboration with the United Nations Children’s Fund (UNICEF), as part of the global MICS4 programme. Technical and financial support was provided by UNICEF.

MICS provides up-to-date information on the situation of children and women and measures key indicators that allow countries to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments.

OBJECTIVES

• To provide up-to-date information for assessing the situation of children and women in Trinidad and Tobago;

• To furnish data needed for monitoring progress towards goals established in the national development plans and internationally agreed upon commitments, as a basis for future action;

• To collect disaggregated data for the identification of inequities and disparities, to allow for evidence based policy-making aimed at social inclusion of the most vulnerable;

• To contribute to the improvement of data and monitoring systems in Trinidad and Tobago and to strengthen technical expertise in the design, collection and analysis of data;

• To validate data from other sources and the results of focused interventions.

Geographic coverage

National level and for 5 Regional Health Authorities (regions): North West, North Central, South West, East, and Tobago.

Analysis unit

• Individuals

• Households

Universe

The survey covered all de jure household members (usual residents), all women age 15-49 years and all children under 5 living in the Household.

Kind of data

Sample survey data [ssd]

Sampling procedure

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample.

SAMPLE SIZE AND SAMPLE ALLOCATION

The sample size for the Trinidad and Tobago 2011 MICS was calculated as 6,600 households. For the calculation of the sample size, the key indicator used was DPT (diphtheria, pertussis and tetanus) immunization coverage.

For each of the five regions, namely, North West, North Central, South West, East and Tobago, the calculation of n was based on r (DPT coverage) that was assumed to be 72.9 percent, 70.3 percent, 87 percent, 94.5 percent and 77.8 percent respectively, based on the values found in Trinidad and Tobago 2006 MICS.

The choice of the DPT immunization rate as the key indicator for estimating sample size was made after examining the likely sample sizes that would be needed for this and other possible key variables such as those relating to HIV.

To calculate n (the required sample size) the r values for DPT for each region were used, p (percentage of children age 18-29 months in the total population) was taken as 3 percent, average household size was taken as 3.4 persons, and the expected response rate was assumed to be 90%. The standard MICS default value of 1.5 was used for the design effect deff, since there was some doubt about the credibility of the very low deff values obtained for DPT in Trinidad and Tobago 2006 MICS.

Given uncertainties that prevailed with respect to the required sample size, the sampling consultant recommended a sample size of 6,600 households for Trinidad and Tobago 2011 MICS, which is slightly larger than the sample size used in Trinidad and Tobago 2006 MICS.

A number of possible allocation principles were considered for determining the number of sampling units to be enumerated in each of the five regions. These included proportional allocation, square root allocation, cube root allocation and equal allocation. Because Trinidad and Tobago 2006 MICS had relied on proportional allocation resulting in sample sizes that were too small to yield reliable estimates in the Eastern region and in Tobago, 2011 MICS relied on disproportionate allocation based on the three alternative allocation principles - a square root allocation, a cube root allocation and an equal allocation.

SAMPLING FRAME AND SELECTION OF CLUSTERS

The survey team examined the possible sampling frames at CSO. One option was a sampling frame based on the old administrative regions consisting of counties and wards, and a table of equivalence that links the former structure to a new set of administrative regions consisting primarily of regional corporations, two cities, three boroughs and the island of Tobago with its seven parishes. The survey team also discussed about using a sampling frame that was developed to undertake work done for the Pan- American Health Organization (PAHO) and which was based on an automatic system for sample selection. It was prepared in December 2009 and consisted of a listing of all the EDs by region, along with their size estimates. The PAHO frame was considered ideal for Trinidad and Tobago 2011 MICS and was used for the selection of clusters.

Separate lists of enumeration districts have been prepared for Trinidad and for Tobago. The lists for Trinidad had to be disaggregated to reflect the four health regions on the island. The lists had to be cleaned as a number of EDs had no measure of size to the extent that it was appropriate to insert the latest available figure, from either the 2000 census or some more recent survey. A few EDs were extremely small and had to be combined with neighboring EDs before the sample was drawn. In contrast, some other EDs were very large, and had to be segmented, either in the frame before drawing the sample or in the field if a large ED was selected.

The enumeration districts were defined as primary sampling units (PSUs), and were selected from each of the sampling strata by using systematic pps (probability proportional to size) sampling procedures, based on the number of households in each enumeration district. The first stage of sampling was thus completed by selecting the required number of enumeration districts from each of the five regions.

LISTING ACTIVITIES AND SELECTION OF HOUSEHOLDS

Lists of households were prepared by the listing teams in the field for each enumeration district. The households were then sequentially numbered at the Central Statistical Office from 1 to the total number of households in each ED, and a selection of 15 households in each ED was carried out using random systematic selection procedures.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three sets of questionnaires were used in the survey: 1) a household questionnaire which was used to collect information on all de jure household members (usual residents), the household, and the dwelling; 2) a women’s questionnaire administered in each household to all women age 15-49 years; and 3) an under-5 questionnaire, administered to mothers (or caretakers) for all children under 5 living in the household.

The Questionnaire for Children Under Five was administered to mothers (or caretakers) of children under 5 years of age1 living in households where interviews were conducted. Normally, the questionnaire was administered to mothers of under-5 children; in cases when the mother was not listed in the household roster, a primary caretaker for the child was identified and interviewed.

The questionnaires are based on the MICS4 model questionnaire. From the MICS4 model English version, the questionnaires were customized and pretested during the third quarter of 2011. Based on the results of the pre-test, modifications were made to the wording of the questionnaires.

In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, observed the place for handwashing, and measured the weights and heights of children age under 5 years.

Cleaning operations

Data were entered using the CSPro software. The data were entered on 10 microcomputers and carried out by 10 data entry operators. There were also a data processing supervisor, a data entry supervisor and 3 secondary editors to reinforce quality control standards. All questionnaires were double-entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS4 programme and adapted to the Trinidad and Tobago questionnaire were used throughout. Data processing began simultaneously with data collection on November 14th, 2011 and was completed in June 2012. According to the original schedule of activities, the completion date for data processing was January 13th, 2012. The delays in completion were mainly due to: incomplete questionnaires, discrepancies in the data, slow pace of some data entry operators, and non-adherence to the data processing process. Data were analysed using the Statistical Package for Social Sciences (SPSS) software program, Version 18. Model syntax and tabulation plans developed by UNICEF were customized and used for this purpose.

Response rate

• Household response rate 92.6

• Women’s overall response rate 86.3

• Under-5’s overall response rate 90.7

Sampling error estimates

The sample of respondents selected in the 2011 Trinidad and Tobago Multiple Indicator Cluster Survey is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey data.

BackgroundSCI is a time-sensitive debilitating neurological condition without treatment options. Although the central nervous system is not programmed for effective endogenous repairs or regeneration, neuroplasticity partially compensates for the dysfunction consequences of SCI.Objective and hypothesisThe purpose of our study is to investigate whether early induction of hypothermia impacts neuronal tissue compensatory mechanisms. Our hypothesis is that although neuroplasticity happens within the neuropathways, both above (forelimbs) and below (hindlimbs) the site of spinal cord injury (SCI), hypothermia further influences the upper limbs’ SSEP signals, even when the SCI is mid-thoracic.Study designA total of 30 male and female adult rats are randomly assigned to four groups (n = 7): sham group, control group undergoing only laminectomy, injury group with normothermia (37°C), and injury group with hypothermia (32°C +/-0.5°C).MethodsThe NYU-Impactor is used to induce mid-thoracic (T8) moderate (12.5 mm) midline contusive injury in rats. Somatosensory evoked potential (SSEP) is an objective and non-invasive procedure to assess the functionality of selective neuropathways. SSEP monitoring of baseline, and on days 4 and 7 post-SCI are performed.ResultsStatistical analysis shows that there are significant differences between the SSEP signal amplitudes recorded when stimulating either forelimb in the group of rats with normothermia compared to the rats treated with 2h of hypothermia on day 4 (left forelimb, p = 0.0417 and right forelimb, p = 0.0012) and on day 7 (left forelimb, p = 0.0332 and right forelimb, p = 0.0133) post-SCI.ConclusionOur results show that the forelimbs SSEP signals from the two groups of injuries with and without hypothermia have statistically significant differences on days 4 and 7. This indicates the neuroprotective effect of early hypothermia and its influences on stimulating further the neuroplasticity within the upper limbs neural network post-SCI. Timely detection of neuroplasticity and identifying the endogenous and exogenous factors have clinical applications in planning a more effective rehabilitation and functional electrical stimulation (FES) interventions in SCI patients.

The Centralized Traffic Control Systems (CTCS) market is an essential component of modern urban infrastructure, revolutionizing the management of traffic flow and enhancing public safety. These advanced systems allow for the centralized monitoring and coordination of traffic signals and controls across extensive net

Abstract

The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular. MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.

The 2006 Iraq Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Iraq; - To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals and the goals of A World Fit For Children (WFFC) as a basis for future action; - To contribute to the improvement of data and monitoring systems in Iraq and to strengthen technical expertise in the design, implementation and analysis of such systems.

Survey Content MICS questionnaires are designed in a modular fashion that was customized to the needs of the country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.

Survey Implementation The survey was implemented by the Central Organization for Statistics and Information Technology (COSIT), the Kurdistan Region Statistics Office (KRSO) and Suleimaniya Statistical Directorate (SSD), in partnership with the Ministry of Health (MOH). The survey also received support and assistance of UNICEF and other partners. Technical assistance and training for the surveys was provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

Geographic coverage

The survey is nationally representative and covers the whole of Iraq.

Analysis unit

Households (defined as a group of persons who usually live and eat together)

De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)

Women aged 15-49

Children aged 0-4

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household. The survey also includes a full birth history listing all chuldren ever born to ever-married women age 15-49 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the Iraq Multiple Indicator Cluster Survey was designed to provide estimates on a large number of indicators on the situation of children and women at the national level; for areas of residence of Iraq represented by rural and urban (metropolitan and other urban) areas; for the18 governorates of Iraq; and also for metropolitan, other urban, and rural areas for each governorate. Thus, in total, the sample consists of 56 different sampling domains, that includes 3 sampling domains in each of the 17 governorates outside the capital city Baghdad (namely, a metropolitan area domain representing the governorate city centre, an other urban area domain representing the urban area outside the governorate city centre, and a rural area domain) and 5 sampling domains in Baghdad (namely, 3 metropolitan areas representing Sadir City, Resafa side, and Kurkh side, an other urban area sampling domain representing the urban area outside the three Baghdad governorate city centres, and a sampling domain comprising the rural area of Baghdad).

The sample was selected in two stages. Within each of the 56 sampling domains, 54 PSUs were selected with linear systematic probability proportional to size (PPS).

\After mapping and listing of households were carried out within the selected PSU or segment of the PSU, linear systematic samples of six households were drawn. Cluster sizes of 6 households were selected to accommodate the current security conditions in the country to allow the surveys team to complete a full cluster in a minimal time. The total sample size for the survey is 18144 households. The sample is not self-weighting. For reporting national level results, sample weights are used.

The sampling procedures are more fully described in the sampling appendix of the final report and can also be found in the list of technical documents within this archive.

(Extracted from the final report: Central Organisation for Statistics & Information Technology and Kurdistan Statistics Office. 2007. Iraq Multiple Indicator Cluster Survey 2006, Final Report. Iraq.)

Sampling deviation

No major deviations from the original sample design were made. One cluster of the 3024 clusters selected was not completed all othe clusters were accessed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires were based on the third round of the Multiple Indicator Cluster survey model questionnaires. From the MICS-3 model English version, the questionnaires were revised and customized to suit local conditions and translated into Arabic and Kurdish languages. The Arabic language version of the questionnaire was pre-tested during January 2006 while the Kurdish language version was pre-tested during March 2006. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, and measured the weights and heights of children age under-5 years.

Cleaning operations

Data were processed in clusters, with each cluster being processed as a complete unit through each stage of data processing. Each cluster goes through the following steps: 1) Questionnaire reception 2) Office editing and coding 3) Data entry 4) Structure and completeness checking 5) Verification entry 6) Comparison of verification data 7) Back up of raw data 8) Secondary editing 9) Edited data back up

After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files: 10) Export to SPSS in 5 files (hh - household, hl - household members, wm - women age 15-49, ch - children under 5 bh - women age 15-49) 11) Recoding of variables needed for analysis 12) Adding of sample weights 13) Calculation of wealth quintiles and merging into data 14) Structural checking of SPSS files 15) Data quality tabulations 16) Production of analysis tabulations

Detailed documentation of the editing of data can be found in the data processing guidelines in the MICS Manual (http://www.childinfo.org/mics/mics3/manual.php)

Data entry was conducted by 12 data entry operators in tow shifts, supervised by 2 data entry supervisors, using a total of 7 computers (6 data entry computers plus one supervisors computer). All data entry was conducted at the GenCenStat head office using manual data entry. For data entry, CSPro version 2.6.007 was used with a highly structured data entry program, using system controlled approach, that controlled entry of each variable. All range checks and skips were controlled by the program and operators could not override these. A limited set of consistency checks were also included inthe data entry program. In addition, the calculation of anthropometric Z-scores was also included in the data entry programs for use during analysis. Open-ended responses ("Other" answers) were not entered or coded, except in rare circumstances where the response matched an existing code in the questionnaire.

Structure and completeness checking ensured that all questionnaires for the cluster had been entered, were structurally sound, and that women's and children's questionnaires existed for each eligible woman and child.

100% verification of all variables was performed using independent verification, i.e. double entry of data, with separate comparison of data followed by modification of one or both datasets to correct keying errors by original operators who first keyed the files.

After completion of all processing in CSPro, all individual cluster files were backed up before concatenating data together using the CSPro file concatenate utility.

Data editing took place at a number of stages throughout the processing (see Other processing), including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files

Detailed documentation of the editing of data can be found in the data processing guidelines in the MICS Manual (http://www.childinfo.org/mics/mics3/manual.php)

Response rate

Of the 18144 households selected for the sample, 18123 were found to be occupied. Of these, 17873 were successfully interviewed for a household response rate of 98.6 percent. In the interviewed households, 27564 women (age 15-49 years) were identified. Of these, 27186 were successfully interviewed, yielding a