Abstract

The main objective of the HEIS survey is to obtain detailed data on household expenditure and income, linked to various demographic and socio-economic variables, to enable computation of poverty indices and determine the characteristics of the poor and prepare poverty maps. Therefore, to achieve these goals, the sample had to be representative on the sub-district level. The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality.

Data collected through the survey helped in achieving the following objectives: 1. Provide data weights that reflect the relative importance of consumer expenditure items used in the preparation of the consumer price index 2. Study the consumer expenditure pattern prevailing in the society and the impact of demographic and socio-economic variables on those patterns 3. Calculate the average annual income of the household and the individual, and assess the relationship between income and different economic and social factors, such as profession and educational level of the head of the household and other indicators 4. Study the distribution of individuals and households by income and expenditure categories and analyze the factors associated with it 5. Provide the necessary data for the national accounts related to overall consumption and income of the household sector 6. Provide the necessary income data to serve in calculating poverty indices and identifying the poor characteristics as well as drawing poverty maps 7. Provide the data necessary for the formulation, follow-up and evaluation of economic and social development programs, including those addressed to eradicate poverty

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The Household Expenditure and Income survey sample for 2010, was designed to serve the basic objectives of the survey through providing a relatively large sample in each sub-district to enable drawing a poverty map in Jordan. The General Census of Population and Housing in 2004 provided a detailed framework for housing and households for different administrative levels in the country. Jordan is administratively divided into 12 governorates, each governorate is composed of a number of districts, each district (Liwa) includes one or more sub-district (Qada). In each sub-district, there are a number of communities (cities and villages). Each community was divided into a number of blocks. Where in each block, the number of houses ranged between 60 and 100 houses. Nomads, persons living in collective dwellings such as hotels, hospitals and prison were excluded from the survey framework.

A two stage stratified cluster sampling technique was used. In the first stage, a cluster sample proportional to the size was uniformly selected, where the number of households in each cluster was considered the weight of the cluster. At the second stage, a sample of 8 households was selected from each cluster, in addition to another 4 households selected as a backup for the basic sample, using a systematic sampling technique. Those 4 households were sampled to be used during the first visit to the block in case the visit to the original household selected is not possible for any reason. For the purposes of this survey, each sub-district was considered a separate stratum to ensure the possibility of producing results on the sub-district level. In this respect, the survey framework adopted that provided by the General Census of Population and Housing Census in dividing the sample strata. To estimate the sample size, the coefficient of variation and the design effect of the expenditure variable provided in the Household Expenditure and Income Survey for the year 2008 was calculated for each sub-district. These results were used to estimate the sample size on the sub-district level so that the coefficient of variation for the expenditure variable in each sub-district is less than 10%, at a minimum, of the number of clusters in the same sub-district (6 clusters). This is to ensure adequate presentation of clusters in different administrative areas to enable drawing an indicative poverty map.

It should be noted that in addition to the standard non response rate assumed, higher rates were expected in areas where poor households are concentrated in major cities. Therefore, those were taken into consideration during the sampling design phase, and a higher number of households were selected from those areas, aiming at well covering all regions where poverty spreads.

Mode of data collection

Face-to-face [f2f]

Research instrument

• General form
• Expenditure on food commodities form
• Expenditure on non-food commodities form

Cleaning operations

Raw Data: - Organizing forms/questionnaires: A compatible archive system was used to classify the forms according to different rounds throughout the year. A registry was prepared to indicate different stages of the process of data checking, coding and entry till forms were back to the archive system. - Data office checking: This phase was achieved concurrently with the data collection phase in the field where questionnaires completed in the field were immediately sent to data office checking phase. - Data coding: A team was trained to work on the data coding phase, which in this survey is only limited to education specialization, profession and economic activity. In this respect, international classifications were used, while for the rest of the questions, coding was predefined during the design phase. - Data entry/validation: A team consisting of system analysts, programmers and data entry personnel were working on the data at this stage. System analysts and programmers started by identifying the survey framework and questionnaire fields to help build computerized data entry forms. A set of validation rules were added to the entry form to ensure accuracy of data entered. A team was then trained to complete the data entry process. Forms prepared for data entry were provided by the archive department to ensure forms are correctly extracted and put back in the archive system. A data validation process was run on the data to ensure the data entered is free of errors. - Results tabulation and dissemination: After the completion of all data processing operations, ORACLE was used to tabulate the survey final results. Those results were further checked using similar outputs from SPSS to ensure that tabulations produced were correct. A check was also run on each table to guarantee consistency of figures presented, together with required editing for tables' titles and report formatting.

Harmonized Data: - The Statistical Package for Social Science (SPSS) was used to clean and harmonize the datasets. - The harmonization process started with cleaning all raw data files received from the Statistical Office. - Cleaned data files were then merged to produce one data file on the individual level containing all variables subject to harmonization. - A country-specific program was generated for each dataset to generate/compute/recode/rename/format/label harmonized variables. - A post-harmonization cleaning process was run on the data. - Harmonized data was saved on the household as well as the individual level, in SPSS and converted to STATA format.

Based on previous literature review and combined with clinical manifestations and work experience of brain tumors, a self-designed general information scale was developed, including age, gender, marital status, educational level, monthly family income, payment method for patient medical expenses, time from disease diagnosis to present, current work status, and whether the diagnosis of brain tumors affects retirement age. This study used the Medical Coping Modes Questionnaire (MCMQ) specifically designed for patients, which was developed by Feifel et al. and has been used for cancer, surgery, chronic hepatitis, and gynecological patients. It is also based on the Swiss Jung and Myers scales Briggs Personality Inventory (APESK) is used to standardize the scores of each item in the medical coping questionnaire. This scale includes three dimensions: confidence, avoidance, and resistance, with 20 items. Each item is scored on a scale of 1-4, with 8 items requiring reverse scoring. The higher the score in the dimension, the better the patient's coping strategies for the disease. To ensure the accuracy of the data, Excel software is used for two person input. Use IBM SPSS Statistics 27.0 for data description and analysis. Quantitative data that conforms to normal distribution are expressed as mean ± standard deviation, and one-way analysis uses independent sample t-test or one-way ANOVA test; If the measurement data does not conform to a normal distribution, the median Q2 (Q1, Q3) (Q1 is the lower quartile, Q2 is the median, Q3 is the upper quartile) is used to represent it. For univariate analysis, the Kruskal Wallis test, a non parametric test, is used; Perform multiple factor analysis using multiple linear regression. P<0.05 is considered statistically significant.

Este artículo analiza los patrones ofensivos después de los tiempos muertos (ATOs) en momentos críticos de los partidos de la temporada 2022/23 de la EuroLeague masculina. Utilizando metodología observacional y herramientas estadísticas avanzadas, se evaluaron 365 ATOs de 169 partidos cerrados (diferencia final de 10 puntos o menos). Los hallazgos destacan que los equipos líderes finalizan las jugadas con mayor éxito a través de tiros libres tras faltas, mientras que los equipos perdedores tienden a emplear estrategias ofensivas más rápidas, como bandejas y triples. Estos resultados ofrecen a entrenadores y personal técnico información clave para optimizar decisiones tácticas en momentos de alta presión. Además, el estudio subraya la importancia de entrenar estas jugadas en condiciones que simulen la intensidad física y psicológica de la competición real.En el directorio se encuentran tres archivos. En el subdirectorio SPSS se incluye el archivo de la base de datos diseñado para su uso con el software IBM SPSS (Statistical Package for the Social Sciences). Por otro lado, en el subdirectorio THEME6 se encuentran dos archivos compatibles con el programa Theme 6 Edu para la búsqueda de T-Patterns. Si se utiliza Theme 5, será necesario añadir al archivo VVT el criterio "Inicio-Fin" con las categorías : y &. De no realizar esta modificación, el archivo no funcionará correctamente.---------------------------This article examines offensive patterns after timeouts (ATOs) during critical moments of the 2022/23 men's EuroLeague season. Using observational methodology and advanced statistical tools, 365 ATOs from 169 close-score games (final point difference of 10 or fewer) were analyzed. Findings highlight that leading teams successfully conclude plays through free throws following fouls, while trailing teams often rely on quicker offensive strategies like layups and three-pointers. These insights provide coaches and technical staff with critical information to optimize tactical decisions under high-pressure conditions. The study also emphasizes the importance of training these plays in scenarios that replicate the physical and psychological intensity of real competition.In the directory, three files are available. The SPSS subdirectory contains the database file for use with IBM's Statistical Package for the Social Sciences (SPSS). Additionally, the THEME6 subdirectory includes two files compatible with the Theme 6 Edu software for T-Pattern analysis. If using Theme 5, the :and & categories must be added to the "Start-End" criterion in the VVT file. Without this adjustment, the file will not function properly.

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

Este estudio analiza los patrones ofensivos y el rendimiento durante momentos críticos en el baloncesto masculino de élite, centrándose en escenarios de una sola posesión en el último minuto y las prórrogas de los partidos de la Euroliga. Utilizando una metodología observacional con herramientas estadísticas avanzadas (análisis de patrones T y pruebas de chi-cuadrado), se examinaron 709 acciones técnico-tácticas. Los resultados destacan la efectividad de los contraataques, las acciones con un mínimo de pases y las jugadas iniciadas por bases y pívots. Además, los tiros libres tras faltas del equipo contrario resultaron ser el desenlace exitoso más frecuente para los equipos que lideraban. Estos hallazgos ofrecen recomendaciones prácticas para optimizar estrategias ofensivas en situaciones de alta presiónEn el directorio se encuentran tres archivos. En el subdirectorio Archivo SPSS/Datos se incluye el archivo de la base de datos diseñado para su uso con el software IBM SPSS (Statistical Package for the Social Sciences). Por otro lado, en el subdirectorio Archivos/THEME6 se encuentran dos archivos compatibles con el programa Theme 6 Edu para la búsqueda de T-Patterns. Si se utiliza Theme 5, será necesario añadir al archivo VVT el criterio "Inicio-Fin" con las categorías : y &. De no realizar esta modificación, el archivo no funcionará correctamente.---------------------------This study explores offensive patterns and performance during critical moments in elite men's basketball, focusing on one-possession scenarios in the last minute and overtime of EuroLeague games. Using an observational methodology with advanced statistical tools (T-Pattern analysis and chi-square tests), it examines 709 technical-tactical actions. The findings highlight the effectiveness of fast breaks, actions with minimal passing, and plays initiated by point guards and centers. Additionally, free throws following fouls by opponents emerged as the most common successful outcome for leading teams. These results provide actionable insights for optimizing offensive strategies under high-pressure conditions.In the directory, three files are available. The Archivo SPSS/Datos subdirectory contains the database file for use with IBM's Statistical Package for the Social Sciences (SPSS). Additionally, the Archivos/THEME6 subdirectory includes two files compatible with the Theme 6 Edu software for T-Pattern analysis. If using Theme 5, the :and & categories must be added to the "Start-End" criterion in the VVT file. Without this adjustment, the file will not function properly.

Abstract

The basic goal of this survey is to provide the necessary database for formulating national policies at various levels. It represents the contribution of the household sector to the Gross National Product (GNP). Household Surveys help as well in determining the incidence of poverty, and providing weighted data which reflects the relative importance of the consumption items to be employed in determining the benchmark for rates and prices of items and services. Generally, the Household Expenditure and Consumption Survey is a fundamental cornerstone in the process of studying the nutritional status in the Palestinian territory.

The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality. Data is a public good, in the interest of the region, and it is consistent with the Economic Research Forum's mandate to make micro data available, aiding regional research on this important topic.

Geographic coverage

The survey data covers urban, rural and camp areas in West Bank and Gaza Strip.

Analysis unit

1- Household/families. 2- Individuals.

Universe

The survey covered all the Palestinian households who are a usual residence in the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample and Frame:

The sampling frame consists of all enumeration areas which enumerated in 1997 and the numeration area consists of buildings and housing units and has in average about 150 households in it. We use the enumeration areas as primary sampling units PSUs in the first stage of the sampling selection. The enumeration areas of the master sample were updated in 2003.

Sample Design:

The sample is stratified cluster systematic random sample with two stages: The calculated sample size is 1,616 households, the completed households were 1,281 (847 in the west bank and 434 in the Gaza strip). First stage: selection a systematic random sample of 120 enumeration areas. Second stage: selection a systematic random sample of 12-18 households from each enumeration area selected in the first stage.

Sample strata:

We divided the population by: 1- Region (North West Bank, Middle West Bank, South West Bank, Gaza Strip) 2- Type of Locality (urban, rural, refugee camps)

Target cluster size:

The target cluster size or "sample-take" is the average number of households to be selected per PSU. In this survey, the sample take is around 12 households.

Sample Size:

The calculated sample size is 1,616 households, the completed households were 1,281 (847 in the west bank and 434 in the Gaza strip).

Mode of data collection

Face-to-face [f2f]

Research instrument

The PECS questionnaire consists of two main sections:

First section: Certain articles / provisions of the form filled at the beginning of the month, and the remainder filled out at the end of the month. The questionnaire includes the following provisions:

Cover sheet: It contains detailed and particulars of the family, date of visit, particular of the field/office work team, number/sex of the family members.

Statement of the family members: Contains social, economic and demographic particulars of the selected family.

Statement of the long-lasting commodities and income generation activities: Includes a number of basic and indispensable items (i.e., Livestock, or agricultural lands).

Housing Characteristics: Includes information and data pertaining to the housing conditions, including type of house, number of rooms, ownership, rent, water, electricity supply, connection to the sewer system, source of cooking and heating fuel, and remoteness/proximity of the house to education and health facilities.

Monthly and Annual Income: Data pertaining to the income of the family is collected from different sources at the end of the registration / recording period.

Assistance and poverty: includes questions about household conditions and assistances that got through the the past month.

Second section: The second section of the questionnaire includes a list of 55 consumption and expenditure groups itemized and serially numbered according to its importance to the family. Each of these groups contains important commodities. The number of commodities items in each for all groups stood at 667 commodities and services items. Groups 1-21 include food, drink, and cigarettes. Group 22 includes homemade commodities. Groups 23-45 include all items except for food, drink and cigarettes. Groups 50-55 include all of the long-lasting commodities. Data on each of these groups was collected over different intervals of time so as to reflect expenditure over a period of one full year, except the cars group the data of which was collected for three previous years. These data was abotained from the recording book which is covered a period of month for each household.

Cleaning operations

Raw Data

Data editing took place though a number of stages, including: 1. Office editing and coding 2. Data entry 3. Structure checking and completeness 4. Structural checking of SPSS data files

Harmonized Data

• The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets.
• The harmonization process starts with cleaning all raw data files received from the Statistical Office.
• Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/compute/recode/rename/format/label harmonized variables.
• A post-harmonization cleaning process is run on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Response rate

The survey sample consists of about 1,616 households interviewed over a twelve months period between (January 2006-January 2007), 1,281 households completed interview, of which 847 in the West Bank and 434 household in Gaza Strip, the response rate was 79.3% in the Palestinian Territory.

Sampling error estimates

Generally, surveys samples are exposed to two types of errors. The statistical errors, being the first type, result from studying a part of a certain society and not including all its sections. And since the Household Expenditure and Consumption Surveys are conducted using a sample method, statistical errors are then unavoidable. Therefore, a potential sample using a suitable design has been employed whereby each unit of the society has a high chance of selection. Upon calculating the rate of bias in this survey, it appeared that the data is of high quality. The second type of errors is the non-statistical errors that relate to the design of the survey, mechanisms of data collection, and management and analysis of data. Members of the work commission were trained on all possible mechanisms to tackle such potential problems, as well as on how to address cases in which there were no responses (representing 9.6%).

This article presents a detailed notational analysis of women’s pickleball, focusing on the technical-tactical aspects that define performance in the sport. The study examines the court zones most utilized during points and the types of shots that determine point outcomes, such as forehands, backhands, and volleys. Through the analysis of 15 matches from five tournaments of the 2023 PPA Pro Tour, common gameplay patterns and significant differences in shot execution between women and men are identified. The results suggest that, while both genders display a combination of baseline and net strategies, women tend to focus more on baseline shots. Additionally, a high incidence of unforced errors is observed, emphasizing the importance of consistency and accuracy in play. Finally, the article provides practical applications to improve pickleball performance based on the observed findings.In the directory, three files are available. The SPSS subdirectory contains the database file for use with IBM's Statistical Package for the Social Sciences (SPSS). Additionally, the THEME6 subdirectory includes two files compatible with the Theme 6 Edu software for T-Pattern analysis. If using Theme 5, the :and & categories must be added to the "Start-End" criterion in the VVT file. Without this adjustment, the file will not function properly.--------------Este artículo presenta un análisis notacional detallado de la categoría femenina de pickleball, centrándose en los aspectos técnico-tácticos que definen el rendimiento en este deporte. Se examinan las zonas de la pista más utilizadas durante los puntos y los tipos de golpes que determinan el desenlace de las jugadas, como los golpes de derecha, revés y voleas. A través del análisis de 15 partidos de cinco torneos del PPA Pro Tour 2023, se identifican patrones de juego comunes y diferencias significativas en la ejecución de los golpes entre mujeres y hombres. Los resultados sugieren que, aunque ambos géneros muestran una combinación de tácticas de fondo y de red, las jugadoras tienden a centrarse más en los golpes de fondo. Además, se destaca la alta incidencia de errores no forzados, lo que subraya la importancia de la consistencia y precisión en el juego. Finalmente, el artículo ofrece aplicaciones prácticas para mejorar el rendimiento en pickleball, basadas en los hallazgos observados.En el directorio se encuentran tres archivos. En el subdirectorio SPSS se incluye el archivo de la base de datos diseñado para su uso con el software IBM SPSS (Statistical Package for the Social Sciences). Por otro lado, en el subdirectorio THEME6 se encuentran dos archivos compatibles con el programa Theme 6 Edu para la búsqueda de T-Patterns. Si se utiliza Theme 5, será necesario añadir al archivo VVT el criterio "Inicio-Fin" con las categorías : y &. De no realizar esta modificación, el archivo no funcionará correctamente.

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.

Survey Objectives The 2005 Ukraine Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Ukraine - To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Ukraine 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 can be easily customized to the needs of a 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 surveys is carried out by the State Statistics Committee of Ukraine, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is 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 Ukraine.

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.

Kind of data

Sample survey data [ssd]

Sampling procedure

The principal objective of the sample design was to provide current and reliable estimates on a set of indicators covering the four major areas of the World Fit for Children declaration, including promoting healthy lives; providing quality education; protecting against abuse, exploitation and violence; and combating HIV/AIDS. The population covered by the 2005 MICS is defined as the universe of all women aged 15-49 and all children aged under 5. A sample of households was selected and all women aged 15-49 identified as usual residents of these households were interviewed. In addition, the mother or the caretaker of all children aged under 5 who were usual residents of the household were also interviewed about the child.

The 2005 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2005 MICS was to prodvide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole, and for urban and rural areas separately. Administrative units of the country are called oblast, there are 24 oblasts in the country plus AR Crimea and Kyiv. Each oblast is devided into rayons (which can be urban and rural) and cities. In addtion, each rayon or city, according to the 2001 census, was subdivided into instruction units. In total Ukraine includes 38,091 instruction units. The sample frame for this survey was based on the list of instruction units developed from the 2001 population census.

The primary sampling unit (PSU), the cluster for the 2005 MICS, is defined on the basis of the instruction units from the census frame.

The three-stage sampling was implemented. At the first stage of the selection process 100 primary selection units (cities or rural rayons) were selected with a probability proportional to the country population. At the second stage of selection secondary selection units (National Census 2001 instruction units) were selected; one in each selected city or rural rayon. The selection at the second was implemented proportionally to the population of the instruction units. At the third stage two lists of households were compiled in every instruction unit (secondary selection units). The first list included households with children under 5 and the second contained all the rest of households. 28 households with children aged 0-4 and 28 other households were systematically selected in each of the two lists in every secondary selection unit.

The sample is stratified by region and is not self-weighted. Sample weights were used when preparing the reports at the national level.

Following standard MICS data collection rules, if a household was actually more than one household when visited, then a) if the selected household contained two households, both were interviewed, or b) if the selected household contained 3 or more households, then only the household of the person named as the head was interviewd.

No replacement of households was permitted in case of non-response or non-contactable households. Adjustments were made to the sampling weights to correct for non-response, according to MICS standard procedures.

The sampling procedures are more fully described in the sampling design document and will be provided at the sampling appendix of the final report, once it is finished.

Sampling deviation

No major deviations from the original sample design were made. All sample enumeration areas were accessed and successfully interviewed with good response rates.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Ukraine MICS were structured questionnaires based on the MICS3 Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status. The household questionnaire includes household listing, education, water and sanitation, household characteristics, child labour, child discipline and salt iodization.

In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire was administered to the mother or caretaker of the child.

The women's questionnaire includes women's characteristics, child mortality, maternal and newborn health, marriage and union, security of tenure, contraception, domestic violence and HIV/AIDS knowledge.

The children's questionnaire includes children's characteristics, birth registration and early learning, child development, breastfeeding and care of illness.

The questionnaires were developed in English from the MICS3 Model Questionnaires, and were translated into Ukrainian and Russian.

The Ukrainian and Russian questionnaires were both piloted as part of the survey pretest.

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 4 files (hh - household, hl - household members, wm - women, ch - children under 5) 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

Details of each of these steps can be found in the data processing documentation, data editing guidelines, data processing programs in CSPro and SPSS, and tabulation guidelines.

The data were entered on 26 microcomputers and carried out by 26 data entry operators and 26 data entry supervisors. All data entry was conducted at the Oblast' s Statistics offices 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

A pesar del creciente auge del baloncesto femenino en los últimos años, la literatura científica sobre este tema sigue siendo considerablemente menos extensa en comparación con su contraparte masculina. El objetivo principal de esta investigación fue analizar las acciones y patrones ofensivos exitosos durante momentos críticos en la EuroLiga Femenina. La muestra consistió en 377 acciones técnico-tácticas correspondientes a jugadas con diferencias de marcador de tres puntos o menos (partidos con una sola posesión de diferencia) en el último minuto y en los periodos de prórroga de la EuroLiga Femenina durante las temporadas 2021/22 y 2022/23. Este estudio se basó en un diseño observacional, utilizando el software LINCE PLUS junto con una herramienta de observación personalizada. Se realizaron estadísticas descriptivas y pruebas de chi-cuadrado (χ²) utilizando el software SPSS versión 25, mientras que la detección de patrones temporales (T-Pattern) se llevó a cabo mediante el software Theme 5. Se estableció un umbral de significancia estadística en p < 0,05. Los hallazgos indicaron que los equipos locales lograron un mayor porcentaje de jugadas exitosas en comparación con los equipos visitantes. La mayoría de los patrones exitosos ocurrieron durante la fase final de la posesión (entre los 8 y 0 segundos), independientemente de la localización del partido o del resultado del equipo. Además, las bandejas, las jugadas que involucraban tiros tras bloqueos directos y las acciones posteriores a faltas personales demostraron las tasas de éxito más altas. Las implicaciones prácticas discutidas en esta investigación ofrecen valiosas perspectivas para que los entrenadores optimicen las estrategias ofensivas durante momentos de alta presión en el baloncesto femenino de élite.En el directorio se encuentran tres archivos. En el subdirectorio Archivo SPSS/Datos se incluye el archivo de la base de datos diseñado para su uso con el software IBM SPSS (Statistical Package for the Social Sciences). Por otro lado, en el subdirectorio Archivos/THEME6 se encuentran dos archivos compatibles con el programa Theme 6 Edu para la búsqueda de T-Patterns. Si se utiliza Theme 5, será necesario añadir al archivo VVT el criterio "Inicio-Fin" con las categorías : y &. De no realizar esta modificación, el archivo no funcionará correctamente.---------------------------Despite the growing popularity of women’s basketball in recent years, scientific literature on the subject remains significantly less extensive compared to its male counterpart. The main objective of this research was to analysze successful offensive actions and patterns during critical moments in the Women’s EuroLeague. The sample consisted of 377 technical-–tactical actions corresponding to plays with score differences of three points or less (one-possession games) in the final minute and overtime periods of the Women’s EuroLeague during the 2021/22 and 2022/23 seasons. Thise study was based on an observational design, utilizing the LINCE PLUS software together with a customized observation tool. Descriptive statistics and chi-square (χ2) tests were carried out using SPSS version 25, while T-Pattern detection was performed through Theme 5 software. A threshold for statistical significance was established at p < 0.05. The findings indicated that home teams achieved a higher percentage of successful plays compared to visiting teams. Most successful patterns occurred during the final phase of possession (8”–0”), regardless of game location or team result. Additionally, layups, plays involving shots after on- ball screen, and actions following personal fouls demonstrated the highest success rates. The practical implications discussed in this research provide valuable insights for coaches to optimize offensive strategies during high-pressure moments in elite women’s basketball.In the directory, three files are available. The Archivo SPSS/Datos subdirectory contains the database file for use with IBM's Statistical Package for the Social Sciences (SPSS). Additionally, the Archivos/THEME6 subdirectory includes two files compatible with the Theme 6 Edu software for T-Pattern analysis. If using Theme 5, the :and & categories must be added to the "Start-End" criterion in the VVT file. Without this adjustment, the file will not function properly.FundingThis study was funded by the Ministerio de Cultura y Deporte (https://www.culturaydeporte.gob.es/portada.html), Consejo Superior de Deportes (https://www.csd.gob.es/es (accessed on 20 June 2024)), and European Union (https://european-union.europa.eu/index_es (accessed on 20 June 2024)) under Project “Integración entre datos observacionales y datos provenientes de sensores externos: Evolución del software LINCE PLUS y desarrollo de la aplicación móvil para la optimización del deporte y la actividad física beneficiosa para la salud (2023)” EXP_74847 to A.G.-S. and I.P.-L. This research was funded by the Universidade de Vigo through a predoctoral fellowship awarded to C.V.-E. (Axudas Predoutorais para a formación de Doutoras/es 2022, Universidade de Vigo. P.P. 00VI 131H 6410211).