The OECD Programme for International Student Assessment (PISA) surveys collected data on students’ performances in reading, mathematics and science, as well as contextual information on students’ background, home characteristics and school factors which could influence performance. This publication includes detailed information on how to analyse the PISA data, enabling researchers to both reproduce the initial results and to undertake further analyses. In addition to the inclusion of the necessary techniques, the manual also includes a detailed account of the PISA 2006 database and worked examples providing full syntax in SPSS.

Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization.

This publication provides all the information required to understand the PISA 2003 educational performance database and perform analyses in accordance with the complex methodologies used to collect and process the data. It enables researchers to both reproduce the initial results and to undertake further analyses. The publication includes introductory chapters explaining the statistical theories and concepts required to analyse the PISA data, including full chapters on how to apply replicate weights and undertake analyses using plausible values; worked examples providing full syntax in SPSS®; and a comprehensive description of the OECD PISA 2003 international database. The PISA 2003 database includes micro-level data on student educational performance for 41 countries collected in 2003, together with students’ responses to the PISA 2003 questionnaires and the test questions. A similar manual is available for SAS users.

GENERAL INFORMATION

Title of Dataset: A dataset from a survey investigating disciplinary differences in data citation

Date of data collection: January to March 2022

Collection instrument: SurveyMonkey

Funding: Alfred P. Sloan Foundation

SHARING/ACCESS INFORMATION

Licenses/restrictions placed on the data: These data are available under a CC BY 4.0 license

Links to publications that cite or use the data:

Gregory, K., Ninkov, A., Ripp, C., Peters, I., & Haustein, S. (2022). Surveying practices of data citation and reuse across disciplines. Proceedings of the 26th International Conference on Science and Technology Indicators. International Conference on Science and Technology Indicators, Granada, Spain. https://doi.org/10.5281/ZENODO.6951437

Gregory, K., Ninkov, A., Ripp, C., Roblin, E., Peters, I., & Haustein, S. (2023). Tracing data:
A survey investigating disciplinary differences in data citation. Zenodo. https://doi.org/10.5281/zenodo.7555266

DATA & FILE OVERVIEW

File List

• Filename: MDCDatacitationReuse2021Codebook.pdf
  Codebook
• Filename: MDCDataCitationReuse2021surveydata.csv
  Dataset format in csv
• Filename: MDCDataCitationReuse2021surveydata.sav
  Dataset format in SPSS
• Filename: MDCDataCitationReuseSurvey2021QNR.pdf
  Questionnaire

Additional related data collected that was not included in the current data package: Open ended questions asked to respondents

METHODOLOGICAL INFORMATION

Description of methods used for collection/generation of data:

The development of the questionnaire (Gregory et al., 2022) was centered around the creation of two main branches of questions for the primary groups of interest in our study: researchers that reuse data (33 questions in total) and researchers that do not reuse data (16 questions in total). The population of interest for this survey consists of researchers from all disciplines and countries, sampled from the corresponding authors of papers indexed in the Web of Science (WoS) between 2016 and 2020.

Received 3,632 responses, 2,509 of which were completed, representing a completion rate of 68.6%. Incomplete responses were excluded from the dataset. The final total contains 2,492 complete responses and an uncorrected response rate of 1.57%. Controlling for invalid emails, bounced emails and opt-outs (n=5,201) produced a response rate of 1.62%, similar to surveys using comparable recruitment methods (Gregory et al., 2020).

Methods for processing the data:

Results were downloaded from SurveyMonkey in CSV format and were prepared for analysis using Excel and SPSS by recoding ordinal and multiple choice questions and by removing missing values.

Instrument- or software-specific information needed to interpret the data:

The dataset is provided in SPSS format, which requires IBM SPSS Statistics. The dataset is also available in a coded format in CSV. The Codebook is required to interpret to values.

DATA-SPECIFIC INFORMATION FOR: MDCDataCitationReuse2021surveydata

Number of variables: 94

Number of cases/rows: 2,492

Missing data codes: 999 Not asked

Refer to MDCDatacitationReuse2021Codebook.pdf for detailed variable information.

The attached data is related to a study with proposes to investigate the burden of bacterial and fungal co-infections outcomes on COVID-19 patients. It is a single-center cross-sectional study of hospitalized COVID-19 patients at Beit-Jala hospital in Palestine. The study included 321 hospitalized patients admitted to the ICU between June 2020 and March 2021 aged ≥20 years,

Background: Diagnosis of co-infections with multiple pathogens among hospitalized COVID-19 patients can be jointly challenging and very essential for appropriate treatment, shortening hospital stay and preventing antimicrobial resistance. This study proposes to investigate the burden of bacterial and fungal co-infections outcomes on COVID-19 patients. It is a single center cross-sectional study of hospitalized COVID-19 patients at Beit-Jala hospital in Palestine.

Methods: The study included 321 hospitalized patients admitted to the ICU between June 2020 and March 2021 aged ≥20 years, with a confirmed diagnosis of COVID-19 via RT-PCR conducted on a nasopharyngeal swab. The patient's information was gathered using graded data forms from electronic medical reports.

Results: The diagnosis of bacterial and fungal infection was proved through the patient`s clinical presentation and positive blood or sputum culture results. All cases had received empirical antimicrobial therapy before the ICU admission, and different regimens during the ICU stay. The rate of bacterial co-infection was 51.1%, mainly from gram-negative isolates (Enterobacter species and K.pneumoniae). The rate of fungal co-infection caused by A.fumigatus was 48.9%, and the mortality rate was 8.1%. However, it is unclear if it had been attributed to SARS-CoV-2 or coincidental.

This is the raw data file with which the analysis of the paper entitled ' Gratefully received, gratefully repaid: the role of perceived fairness in cooperative interactions' was carried out. Please refer to the dataset explanatory document (http://figshare.com/articles/Explanatory_Document_for_the_SPSS_Data_File_of_the_Study/1243735) for details.

This statistic depicts the distribution of tools used to compile data and present analytics and/or reports to management, according to a marketing survey of C-level executives, conducted in December 2015 by Black Ink. As of December 2015, 9 percent of respondents used statistical modeling tools, such as IBM's SPSS or the SAS Institute's Statistical Analysis System package, to compile and present their reports.

A SPSS file with data used in the statistical analysis. Covariates were excluded in the file due to restrictions of the ethical permission. However a complete file is provided for researchers after request at publication@ventorp.com. (SAV)

Abstract

The harmonized data set on health, created and published by the ERF, is a subset of Iraq Household Socio Economic Survey (IHSES) 2012. It was derived from the household, individual and health modules, collected in the context of the above mentioned survey. The sample was then used to create a harmonized health survey, comparable with the Iraq Household Socio Economic Survey (IHSES) 2007 micro data set.

----> Overview of the Iraq Household Socio Economic Survey (IHSES) 2012:

Iraq is considered a leader in household expenditure and income surveys where the first was conducted in 1946 followed by surveys in 1954 and 1961. After the establishment of Central Statistical Organization, household expenditure and income surveys were carried out every 3-5 years in (1971/ 1972, 1976, 1979, 1984/ 1985, 1988, 1993, 2002 / 2007). Implementing the cooperation between CSO and WB, Central Statistical Organization (CSO) and Kurdistan Region Statistics Office (KRSO) launched fieldwork on IHSES on 1/1/2012. The survey was carried out over a full year covering all governorates including those in Kurdistan Region.

The survey has six main objectives. These objectives are:

1. Provide data for poverty analysis and measurement and monitor, evaluate and update the implementation Poverty Reduction National Strategy issued in 2009.
2. Provide comprehensive data system to assess household social and economic conditions and prepare the indicators related to the human development.
3. Provide data that meet the needs and requirements of national accounts.
4. Provide detailed indicators on consumption expenditure that serve making decision related to production, consumption, export and import.
5. Provide detailed indicators on the sources of households and individuals income.
6. Provide data necessary for formulation of a new consumer price index number.

The raw survey data provided by the Statistical Office were then harmonized by the Economic Research Forum, to create a comparable version with the 2006/2007 Household Socio Economic Survey in Iraq. Harmonization at this stage only included unifying variables' names, labels and some definitions. See: Iraq 2007 & 2012- Variables Mapping & Availability Matrix.pdf provided in the external resources for further information on the mapping of the original variables on the harmonized ones, in addition to more indications on the variables' availability in both survey years and relevant comments.

Geographic coverage

National coverage: Covering a sample of urban, rural and metropolitan areas in all the governorates including those in Kurdistan Region.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey was carried out over a full year covering all governorates including those in Kurdistan Region.

Kind of data

Sample survey data [ssd]

Sampling procedure

----> Design:

Sample size was (25488) household for the whole Iraq, 216 households for each district of 118 districts, 2832 clusters each of which includes 9 households distributed on districts and governorates for rural and urban.

----> Sample frame:

Listing and numbering results of 2009-2010 Population and Housing Survey were adopted in all the governorates including Kurdistan Region as a frame to select households, the sample was selected in two stages: Stage 1: Primary sampling unit (blocks) within each stratum (district) for urban and rural were systematically selected with probability proportional to size to reach 2832 units (cluster). Stage two: 9 households from each primary sampling unit were selected to create a cluster, thus the sample size of total survey clusters was 25488 households distributed on the governorates, 216 households in each district.

----> Sampling Stages:

In each district, the sample was selected in two stages: Stage 1: based on 2010 listing and numbering frame 24 sample points were selected within each stratum through systematic sampling with probability proportional to size, in addition to the implicit breakdown urban and rural and geographic breakdown (sub-district, quarter, street, county, village and block). Stage 2: Using households as secondary sampling units, 9 households were selected from each sample point using systematic equal probability sampling. Sampling frames of each stages can be developed based on 2010 building listing and numbering without updating household lists. In some small districts, random selection processes of primary sampling may lead to select less than 24 units therefore a sampling unit is selected more than once , the selection may reach two cluster or more from the same enumeration unit when it is necessary.

Mode of data collection

Face-to-face [f2f]

Research instrument

----> Preparation:

The questionnaire of 2006 survey was adopted in designing the questionnaire of 2012 survey on which many revisions were made. Two rounds of pre-test were carried out. Revision were made based on the feedback of field work team, World Bank consultants and others, other revisions were made before final version was implemented in a pilot survey in September 2011. After the pilot survey implemented, other revisions were made in based on the challenges and feedbacks emerged during the implementation to implement the final version in the actual survey.

----> Questionnaire Parts:

The questionnaire consists of four parts each with several sections: Part 1: Socio – Economic Data: - Section 1: Household Roster - Section 2: Emigration - Section 3: Food Rations - Section 4: housing - Section 5: education - Section 6: health - Section 7: Physical measurements - Section 8: job seeking and previous job

Part 2: Monthly, Quarterly and Annual Expenditures: - Section 9: Expenditures on Non – Food Commodities and Services (past 30 days). - Section 10 : Expenditures on Non – Food Commodities and Services (past 90 days). - Section 11: Expenditures on Non – Food Commodities and Services (past 12 months). - Section 12: Expenditures on Non-food Frequent Food Stuff and Commodities (7 days). - Section 12, Table 1: Meals Had Within the Residential Unit. - Section 12, table 2: Number of Persons Participate in the Meals within Household Expenditure Other Than its Members.

Part 3: Income and Other Data: - Section 13: Job - Section 14: paid jobs - Section 15: Agriculture, forestry and fishing - Section 16: Household non – agricultural projects - Section 17: Income from ownership and transfers - Section 18: Durable goods - Section 19: Loans, advances and subsidies - Section 20: Shocks and strategy of dealing in the households - Section 21: Time use - Section 22: Justice - Section 23: Satisfaction in life - Section 24: Food consumption during past 7 days

Part 4: Diary of Daily Expenditures: Diary of expenditure is an essential component of this survey. It is left at the household to record all the daily purchases such as expenditures on food and frequent non-food items such as gasoline, newspapers…etc. during 7 days. Two pages were allocated for recording the expenditures of each day, thus the roster will be consists of 14 pages.

Cleaning operations

----> Raw Data:

Data Editing and Processing: To ensure accuracy and consistency, the data were edited at the following stages: 1. Interviewer: Checks all answers on the household questionnaire, confirming that they are clear and correct. 2. Local Supervisor: Checks to make sure that questions has been correctly completed. 3. Statistical analysis: After exporting data files from excel to SPSS, the Statistical Analysis Unit uses program commands to identify irregular or non-logical values in addition to auditing some variables. 4. World Bank consultants in coordination with the CSO data management team: the World Bank technical consultants use additional programs in SPSS and STAT to examine and correct remaining inconsistencies within the data files. The software detects errors by analyzing questionnaire items according to the expected parameter for each variable.

----> Harmonized Data:

• The SPSS package is used to harmonize the Iraq Household Socio Economic Survey (IHSES) 2007 with Iraq Household Socio Economic Survey (IHSES) 2012.
• The harmonization process starts with raw data files received from the Statistical Office.
• A program is generated for each dataset to create harmonized variables.
• Data is saved on the household and individual level, in SPSS and then converted to STATA, to be disseminated.

Response rate

Iraq Household Socio Economic Survey (IHSES) reached a total of 25488 households. Number of households refused to response was 305, response rate was 98.6%. The highest interview rates were in Ninevah and Muthanna (100%) while the lowest rates were in Sulaimaniya (92%).

SPSS demystified : a step-by-step guide to successful data analysis : for SPSS version 18.0 is a book. It was written by Ronald D. Yockey and published by Pearson Education in 2011.

This dataset is about book subjects and is filtered where the books includes Adventures in social research : data analysis using SPSS 14.0 and 15.0 for Windows, featuring 10 columns including authors, average publication date, book publishers, book subject, and books. The preview is ordered by number of books (descending).

Abstract

According to the Food and Agricultural Organization (FAO) 123 million Chinese remained undernourished in 2003-2005. That represents 14% of the global total. UNICEF states that 7.2 million of the world's stunted children are located in China. In absolute terms, China continues to rank in the top countries carrying the global burden of under-nutrition. China must-and still can reduce under-nutrition, thus contributing even further to the global attainment of MDG1. In this context that the United Nations Joint Programme, in partnership with the Chinese government, has conducted this study. The key objective is to improve evidence of household food security through a baseline study in six pilot counties in rural China. The results will be used to guide policy and programmes aimed at reducing household food insecurity in the most vulnerable populations in China. The study is not meant to be an exhaustive analysis of the food security situation in the country, but to provide a demonstrative example of food assessment tools that may be replicated or scaled up to other places.

Geographic coverage

Six rural counties

Analysis unit

• Household
• Village

Universe

The survey covered household heads and women between 15-49 years resident of that household. A household is defined as a group of people currently living and eating together "under the same roof" (or in same compound if the household has 2 structures).

Kind of data

Sample survey data [ssd]

Sampling procedure

The required sample size for the survey was calculated using standard sample size calculations with each county representing a stratum. After the sample size was calculated, a two-stage clustering approach was applied. The first stage is the selection of villages using the probability proportional to size (PPS) method to create a self-weighted sample in which larger population clusters (villages) have a greater chance of selection, proportional to their size. Following the selection of the villages, 12 households within the village were selected using simple random selection.

Sampling deviation

Floods and landslides prevented the team from visiting two of the selected villages, one in Wuding and one in Panxian, so they substituted them with replacement villages.

Mode of data collection

Face-to-face [f2f]

Research instrument

The household questionnaire was administered to all households in the survey and included modules on demography, education, migration and remittances, housing and facilities, household assets, agricultural, income activities, expenditure, food sources and consumption, shocks and coping strategies.

The objective of the village questionnaire was to gather contextual information on the six counties for descriptive purposes. In each village visited, a focus group discussion took place on topics including: population of the village, migrants, access to social services such as education and health, infrastructure, access to markets, difficulties facing the village, information on local agricultural practices.

The questionnaires were developed by WFP and Chinese Academy of Agricultural Sciences (CAAS) with inputs from partnering agencies. They were originally formulated in English and then translated into Mandarin. They were pilot tested in the field and corrected as needed. The final interviews were administered in Mandarin with translation provided in the local language when needed.

All questionnaires and modules are provided as external resources.

Cleaning operations

After data collection, data entry was carried out by CAAS staff in Beijing using EpiData software. The datasets were then exported into SPSS for analysis. Data cleaning was an iterative process throughout the data entry and analysis phases.

Descriptive analysis, correlation analysis, principle component analysis, cluster analysis and various other forms of analyses were conducted using SPSS.

Associated data and analysis for scale development of a measurement for map trust. See word document "IJGIS Data Analysis Reproduction Steps" for a full detailing on how to reproduce findings.

Citizen Science (CS) projects play a crucial role in engaging citizens in conservation efforts. While implicitly mostly considered as an outcome of CS participation, citizens may also have a certain attitude toward engagement in CS when starting to participate in a CS project. Moreover, there is a lack of CS studies that consider changes over longer periods of time. Therefore, this research presents two-wave data from four field studies of a CS project about urban wildlife ecology using cross-lagged panel analyses. We investigated the influence of attitudes toward engagement in CS on self-related, ecology-related, and motivation-related outcomes. We found that positive attitudes toward engagement in CS at the beginning of the CS project had positive influences on participants’ psychological ownership and pride in their participation, their attitudes toward and enthusiasm about wildlife, and their internal and external motivation two months later. We discuss the implications for CS research and practice. Dataset for: Greving, H., Bruckermann, T., Schumann, A., Stillfried, M., Börner, K., Hagen, R., Kimmig, S. E., Brandt, M., & Kimmerle, J. (2023). Attitudes Toward Engagement in Citizen Science Increase Self-Related, Ecology-Related, and Motivation-Related Outcomes in an Urban Wildlife Project. BioScience, 73(3), 206–219. https://doi.org/10.1093/biosci/biad003: Analysis script (SPSS Amos format) used for model 1 for all field studies

This study aims to determine "the effect of conflict on employee performance at Giant Pekanbaru". In this study, a sample of 90 people was used. Data collection was carried out through questionnaires and data analysis techniques used with a significance level of 0.05 were validity test, reliability test with crobanchalpha, simple linear regression and t test analysis and analysis of determination R Square (R2). The results of the analysis and data of this study using the help of SPSS Version 16.0, the results of the simple linear regression equation are Y = 45.561 + 0.256X. Based on the results of the research on the t-test showed results, Tcount> Ttable or 2,250> 1,987. So it can be concluded that there is a significant influence between conflict on performance. Based on the data obtained from the variable Y (performance), obtained R Square (R2) of 0.597 or 59.7%. R Square is used to determine the percentage of the influence of the Independent variable (conflict) on the Dependent variable (performance) is 59.7% while the remaining 40.3% is influenced by other variables not examined.

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 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 demograohic 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 chracteristics 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

• Household/families
• Individuals

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2008 Household Expenditure and Income Survey sample was designed using two-stage cluster stratified sampling method. In the first stage, the primary sampling units (PSUs), the blocks, were drawn using probability proportionate to the size, through considering the number of households in each block to be the block size. The second stage included drawing the household sample (8 households from each PSU) using the systematic sampling method. Fourth substitute households from each PSU were drawn, using the systematic sampling method, to be used on the first visit to the block in case that any of the main sample households was not visited for any reason.

To estimate the sample size, the coefficient of variation and design effect in each subdistrict were calculated for the expenditure variable from data of the 2006 Household Expenditure and Income Survey. This results was used to estimate the sample size at sub-district level, provided that the coefficient of variation of the expenditure variable at the sub-district level did not exceed 10%, with a minimum number of clusters that should not be less than 6 at the district level, that is to ensure good clusters representation in the administrative areas to enable drawing poverty pockets.

It is worth mentioning that the expected non-response in addition to areas where poor families are concentrated in the major cities were taken into consideration in designing the sample. Therefore, a larger sample size was taken from these areas compared to other ones, in order to help in reaching the poverty pockets and covering them.

Mode of data collection

Face-to-face [f2f]

Research instrument

List of survey questionnaires: (1) General Form (2) Expenditure on food commodities Form (3) Expenditure on non-food commodities Form

Cleaning operations

Raw Data The design and implementation of this survey procedures were: 1. Sample design and selection 2. Design of forms/questionnaires, guidelines to assist in filling out the questionnaires, and preparing instruction manuals 3. Design the tables template to be used for the dissemination of the survey results 4. Preparation of the fieldwork phase including printing forms/questionnaires, instruction manuals, data collection instructions, data checking instructions and codebooks 5. Selection and training of survey staff to collect data and run required data checkings 6. Preparation and implementation of the pretest phase for the survey designed to test and develop forms/questionnaires, instructions and software programs required for data processing and production of survey results 7. Data collection 8. Data checking and coding 9. Data entry 10. Data cleaning using data validation programs 11. Data accuracy and consistency checks 12. Data tabulation and preliminary results 13. Preparation of the final report and dissemination of final results

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 all 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

Data availability. Multivariate data analysis. Validation of an instrument for the evaluation of teaching digital competence.

• SPSS DATA. Multivariate data analysis. Validation of an instrument for the evaluation of teaching digital competence (spss data.sav). The data presented in this file contains the data imported wiyh the Software IBM SPSS Statistics, versión 28.0.1.1(15).
• EXCEL DATA. Multivariate data analysis. Validation of an instrument for the evaluation of teaching digital competence (spss data.sav). The data presented in this file contains the data imported wiyh the Software IBM SPSS Statistics, versión 28.0.1.1(15).
• Data of Project factorial.xlsx (The data presented in this file contains the results of the statistical analysis carried out with the Software Microsoft Excel).
• Data Project reliability.xlsx (The data presented in this file contains the results of the statistical analysis carried out with the Software Microsoft Excel).
• FIGURES. Multivariate data analysis. Validation of an instrument for the evaluation of teaching digital competence (Figure 1.jpeg, Figure 2.jpeg, Figure 3 and Figure 4.jpeg).

Database of the nation''s substance abuse and mental health research data providing public use data files, file documentation, and access to restricted-use data files to support a better understanding of this critical area of public health. The goal is to increase the use of the data to most accurately understand and assess substance abuse and mental health problems and the impact of related treatment systems. The data include the U.S. general and special populations, annual series, and designs that produce nationally representative estimates. Some of the data acquired and archived have never before been publicly distributed. Each collection includes survey instruments (when provided), a bibliography of related literature, and related Web site links. All data may be downloaded free of charge in SPSS, SAS, STATA, and ASCII formats and most studies are available for use with the online data analysis system. This system allows users to conduct analyses ranging from cross-tabulation to regression without downloading data or relying on other software. Another feature, Quick Tables, provides the ability to select variables from drop down menus to produce cross-tabulations and graphs that may be customized and cut and pasted into documents. Documentation files, such as codebooks and questionnaires, can be downloaded and viewed online.

Code for preprocessing and statistical analysis of neural and behavioral response-response binding data, as described in Geissler, C. F., Frings, C., & Moeller, B. (2021). Illuminating the prefrontal neural correlates of action sequence disassembling in response–response binding. Scientific Reports, 11(1), 1-10. https://doi.org/10.1038/s41598-021-02247-6 Execution of two independent actions in quick succession results in transient binding of these two actions. Subsequent repetition of any of these actions automatically retrieves the other. This process is probably fundamental for developing complex action sequences. However, rigid bindings between two actions are not always adaptive. Sometimes, it is necessary to repeat only one of the two previously executed actions. In such situations, stored action sequences must be disassembled, for the sake of flexibility. Exact mechanisms that allow for such an active unbinding of actions remain largely unknown, but it stands to reason, that some form of prefrontal executive control is necessary. Building on prior neuronal research that explored other forms of binding (e.g. between distractors and responses and abstract representations and responses), we explored middle and superior frontal correlates of -response binding in a sequential classification task with functional near-infrared spectroscopy. We found that anterior dorsolateral prefrontal cortex activity varied as a function of response–repetition condition. Activity in the right anterior dorsolateral prefrontal cortex correlated with changes in reaction times due to response–response binding. Our results indicate that the right anterior dorsolateral prefrontal cortex dismantles bindings between consecutive actions, whenever such bindings interfere with current action goals.: SPSS syntax for behavioral data analysis and correlations between neural and behavioral data