Social sciences -- Statistical methods
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Social sciences -- Statistical methods
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The concept Social sciences -- Statistical methods represents the subject, aboutness, idea or notion of resources found in European University Institute.
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- A Guide for selecting statistical techniques for analyzing social science data
- A first course in Bayesian statistical methods
- A guide for statistics in the behavioral sciences
- A guide to R for social and behavioral science statistics
- A mathematical primer for social statistics
- ANOVA : repeated measures
- Adaptive survey design
- Age-period-cohort models : approaches and analyses with aggregate data
- Agent-based models
- Aggregate data : analysis and interpretation
- Almost all about unit roots : foundations, developments, and applications
- Almost all about unit roots : foundations, developments, and applications
- An introduction to causal analysis in sociology
- An introduction to exponential random graph modeling
- An introduction to exponential random graph modeling
- An introduction to statistics : an active learning approach
- An introduction to survey research and data analysis
- Analysing change : measurement and explanation using longitudinal data
- Analysis of multivariate social science data
- Analysis of nominal data
- Analysis of ordinal data
- Analysis of variance
- Analysis of variance
- Analyzing panel data
- Analyzing qualitative data
- Analyzing quantitative data : an introduction for social researchers
- Analyzing quantitative data : from description to explanation
- Analyzing social science data
- Análisis de la historia de acontecimientos
- Applied linear regression
- Applied meta-analysis for social science research
- Applied multiple regression/correlation analysis for the behavioral sciences
- Applied multivariate research : design and interpretation
- Applied multivariate statistics for the social sciences
- Applied multivariate statistics for the social sciences
- Applied multivariate statistics for the social sciences
- Applied multivariate statistics for the social sciences : analyses with SAS and IBM's SPSS
- Applied regression analysis : doing, interpreting and reporting regression
- Applied regression analysis and generalized linear models
- Applied statistics : from bivariate through multivariate techniques
- Applied statistics I : basic bivariate techniques
- Applied statistics II : multivariable and multivariate techniques
- Applied statistics using stata : a guide for the social sciences
- Applied time series analysis for the social sciences
- Applying the Rasch model : fundamental measurement in the human sciences
- Applying the Rasch model : fundamental measurement in the human sciences
- Assessing inequality
- Assessing inequality
- Basic statistics for social research
- Basics of qualitative research : grounded theory procedures and techniques
- Basics of qualitative research : techniques and procedures for developing grounded theory
- Basics of qualitative research : techniques and procedures for developing grounded theory
- Bayesian analysis for the social sciences
- Bayesian inference in the social sciences
- Bayesian methods : a social and behavioral sciences approach
- Bayesian statistics for the social sciences
- Beginning statistics : an introduction for social scientists
- Beginning statistics : an introduction for social scientists
- Big data and Society
- Big data and social science : a practical guide to methods and tools
- Bootstrapping : a nonparametric approach to statistical inference
- Bootstrapping : a nonparametric approach to statistical inference
- Canonical analysis and factor comparison
- Causal analysis
- Causal analysis with panel data
- Causal modeling
- Central tendency and variability
- Civic engagement and social cohesion : measuring dimensions of social capital to inform policy
- Cluster analysis
- Common problems/proper solutions : avoiding error in quantitative research
- Computer modeling of social processes
- Conceptualization and measurement in the social sciences
- Confidence intervals
- Confidence intervals
- Confirmatory factor analysis : a preface to LISREL
- Confirmatory factor analysis for applied research
- Contrasts and effect sizes in behavioral research : a correlational approach
- Critical statistics : seeing beyond the headlines
- Data Analysis for the Social Sciences : integrating theory and practice
- Data analysis : an introduction
- Data analysis and interpretation
- Data analysis and the social sciences
- Data collection and analysis
- Data collection and analysis
- Data envelopment analysis : theory, methodology, and application
- Data in Society : Challenging Statistics in an Age of Globalisation
- Data mining for the social sciences : an introduction
- Data theory and dimensional analysis
- Demystifying social statistics
- Design and analysis : a researcher's handbook
- Design and analysis of time series experiments
- Designing and conducting survey research : a comprehensive guide
- Differential item functioning
- Differential item functioning
- Discriminant analysis
- Doing secondary analysis
- Easy R : access, prepare, visualize, explore data, and write papers
- Ecological inference
- Ecological inference : new methodological strategies
- Ecological inference : new methodological strategies
- Einführung in die Mehrvariablenanalyse : Grundlagen d. Formulierung u. Prüfung komplexer sozialwiss. Aussagen
- Elementary statistics for the social sciences
- Encompassing : formulation, properties and testing
- Essential maths skills for exploring social data : a student's workbook
- Essential statistics for public managers and policy analysts
- Essentials of statistics for business & economics
- Essentials of statistics for the behavioral sciences
- Ethnostatistics : qualitative foundations for quantitative research
- Event history analysis with R
- Excel 2016 for social science statistics : a guide to solving practical problems
- Exercising essential statistics
- Experimental design and analysis
- Experimental design and the analysis of variance
- Exploratory data analysis
- Exploratory data analysis
- Exploring data : an introduction to data analysis for social scientists
- Fixed effects regression models
- Fonti per le statistiche sociali
- Foundations of behavioral statistics : an insight-based approach
- Foundations of factor analysis
- Fractal analysis
- Fractal analysis
- From numbers to words : reporting statistical results for the social sciences
- Frontiers in massive data analysis
- Fundamental statistics for the social and behavioral sciences
- Fundamentals of behavioral statistics
- Growth modeling : structural equation and multilevel modeling approaches
- Handbook of advanced multilevel analysis
- Handbook of data analysis
- Handbook of data analysis
- Heteroskedasticity in regression : detection and correction
- Hierarchical linear models : applications and data analysis methods
- How to make the world add up
- How to use SPSS syntax : an overview of common commands
- Hypothesen, Gleichungen und Daten : Spezifikations- und Messprobleme bei Kausalmodellen für Daten aus einer und mehreren Beobachtungsperioden
- Hypothesis testing and model selection in the social sciences
- Identification and estimation of latent variables and their effect on social and economic outcomes
- Identification problems in the social sciences
- Identification problems in the social sciences
- Informative hypotheses : theory and practice for behavioral and social scientists
- Interaction effects in factorial analysis of variance
- Interaction effects in multiple regression
- Interaction effects in multiple regression
- Interpreting quantitative data
- Interpreting quantitative data with SPSS
- Interpreting socio-economic data : a foundation of descriptive statistics
- Interrupted time series analysis
- Interrupted time series analysis
- Introduction to applied Bayesian statistics and estimation for social scientists
- Introduction to mediation, moderation, and conditional process analysis : a regression-based approach
- Introduction to meta-analysis
- Introduction to quantitative data analysis in the behavioral, social, and engineering sciences
- Introduction to quantitative research methods : an investigative approach
- Introduction to statistics : an active learning approach
- Introduction to survey sampling
- Introduction to survey sampling
- Introduction to time series analysis
- Introduction to time series analysis
- Introduction to time series analysis and forecasting : with applications in SAS and SPSS
- L'analyse des données : leçons sur l'analyse factorielle et la reconnaissance des formes et travaux du laboratoire de statistique de l'Université de Paris VI
- L'analyse des données : leçons sur l'analyse factorielle et la reconnaissance des formes et travaux du laboratoire de statistique de l'Université de Paris VI | (introduction, théorie, applications diverses, notamment à là nalyse des questionnaires, programmes de calcul), 2, Là nalyse des correspondances
- LISREL approaches to interaction effects in multiple regression
- LISREL approaches to interaction effects in multiple regression
- Latent class and discrete latent trait models : similarities and differences
- Latent growth curve modeling
- Latent growth curve modeling
- Latent variables in socio-economic models
- Logistic regression models for ordinal response variables
- Logit and probit : ordered and multinomial models
- Longitudinal and panel data : analysis and applications in the social sciences
- Longitudinal and panel data : analysis and applications in the social sciences
- Longitudinal data analysis : designs, models and methods
- Longitudinal structural equation modeling
- Making sense of multivariate data analysis
- Markov-switching vector autoregressions : modelling, statistical inference, and application to business cycle analysis
- Mathematical methods in social science
- Mathematics for social scientists
- Maximum likelihood estimation : logic and practice
- Measurement in the social sciences : the link between theory and data
- Measurement in the social sciences : theories and strategies
- Measurement theory and applications for the social sciences
- Measuring the intentional world : realism, naturalism, and quantitative methods in the behavioral sciences
- Methods and applications of statistics in the social and behavioral sciences
- Methods for quantitative macro-comparative research
- Methods for quantitative macro-comparative research
- Methods of meta-analysis : correcting error and bias in research findings
- Methods of meta-analysis : correcting error and bias in research findings
- Modeling and interpreting interactive hypotheses in regression analysis
- Models for social networks with statistical applications
- Modern methods for robust regression
- Modern regression techniques using R : a practical guide for students and researchers
- Modern statistics for the social and behavioral sciences : a practical introduction
- Monte Carlo simulation
- Monte Carlo simulation and resampling : methods for social science
- Multilevel analysis : techniques and applications
- Multilevel analysis : techniques and applications
- Multilevel modeling using R
- Multilevel modeling using R
- Multilevel modeling using R
- Multiple and generalized nonparametric regression
- Multiple comparisons
- Multiple correspondence analysis for the social sciences
- Multiple indicators : an introduction
- Multiple regression in practice
- Multiple regression in practice
- Multivariable modeling and multivariate analysis for the behavioral sciences
- Multivariate analysis for the behavioral sciences
- Multivariate general linear models
- Multivariate tests for time series models
- New developments in categorical data analysis for the social and behavioral sciences
- New developments in statistics for psychology and the social sciences
- Nonparametric measures of association
- Nonparametric statistics for social and behavioral sciences
- Nonparametric statistics for the behavioral sciences
- Nonrecursive causal models
- Nonsampling error in social surveys
- Observing interaction : an introduction to sequential analysis
- Odds ratios in the analysis of contingency tables
- Odds ratios in the analysis of contingency tables
- Ordinal data modeling
- Polytomous item response theory models
- Polytomous item response theory models
- Presenting your data with SPSS explained
- Probability and social science : methodological relationships between the two approaches
- Propensity score analysis : fundamentals and developments
- Propensity score analysis : statistical methods and applications
- Q methodology
- Q methodology
- Q methodology
- Qualitative Analysis for Social Scientists
- Qualitative analysis for social scientists
- Qualitative data analysis : practical strategies
- Quantile regression
- Quantitative research methods for professionals
- Quantitative research methods in the social sciences
- Quick guide to IBM® SPSS® : statistical analysis with step-by-step examples
- Random factors in ANOVA
- Rasch models for measurement
- Rasch models for measurement
- Reasoning with statistics : how to read quantitative research
- Regression analysis : a constructive critique
- Regression analysis and linear models : concepts, applications, and implementation
- Regression diagnostics
- Regression diagnostics : an introduction
- Regression models : censored, sample selected or truncated data
- Regression models for categorical, count, and related variables : an applied approach
- Regression with dummy variables
- Reliability and validity assessment
- Research design : qualitative & quantitative approaches
- Research design : qualitative, quantitative, and mixed method approaches
- Research design : qualitative, quantitative, and mixed methods approaches
- Research design : qualitative, quantitative, and mixed methods approaches
- Running regressions : a practical guide to quantitative research in economics, finance and development studies
- SAGE secondary data analysis
- SPSS Base 9.0 applications guide
- SPSS Base 9.0 user's guide
- SPSS Regression Models 9.0
- SPSS advanced models 9.0
- SPSS for social scientists
- SPSS statistics 17.0 : advanced statistical procedures companion
- Sage handbook of survey methodology
- Schaum's outline of theory and problems of statistics and econometrics
- Science outside the laboratory : measurement in field science and economics
- Secondary analysis of survey data
- Serious stats : a guide to advanced statistics for the behavioral sciences
- Simple statistics : applications in social research
- Social choice with partial knowledge of treatment response
- Social measurement
- Social statistics : managing data, conducting analyses, presenting results
- Social statistics for a diverse society
- Some British empiricists in the social sciences, 1650-1900
- Sorting data : collection and analysis
- Spatial regression models for the social sciences
- Spline regression models
- Spline regression models
- Starting statistics : a short, clear guide
- Statistical analysis of continuous data
- Statistical analysis of social data
- Statistical analysis quick reference guidebook : with SPSS examples
- Statistical decomposition analysis : With applications in the social and administrative sciences
- Statistical games and human affairs : the view from within
- Statistical methods for categorical data analysis
- Statistical methods for social scientists
- Statistical methods for the social & behavioural sciences : a model-based approach
- Statistical methods for the social sciences
- Statistical methods for the social sciences
- Statistical modeling and inference for social science
- Statistical modelling for social researchers : principles and practice
- Statistical models and causal inference : a dialogue with the social sciences
- Statistical persuasion : how to collect, analyze, and present data-- accurately honestly, and persuasively
- Statistical power analysis with missing data : a structural equation modeling approach
- Statistical reasoning in the behavioral sciences
- Statistics : a tool for social research
- Statistics for research : with a guide to SPSS
- Statistics for social data analysis
- Statistics for social data analysis
- Statistics for social sciences
- Statistics for the behavioral sciences
- Statistics for the behavioral sciences
- Statistics for the social sciences
- Statistics in the social sciences : current methodological developments
- Statistics, a tool for social research
- Strategies to approximate random sampling and assignment
- Structural equation modeling : foundations and extensions
- Structural equation modeling with LISREL : essentials and advances
- Studies in econometrics, time series, and multivariate statistics
- Survey sampling and multivariate analysis for social scientists and engineers
- Survival analysis
- Test item bias
- Tests of significance
- The Dimensions of quantitative research in history
- The SAGE handbook of measurement
- The SAGE handbook of quantitative methodology for the social sciences
- The SPSS guide to data analysis
- The SPSS guide to data analysis for SPSSx
- The analysis of cross-classifications
- The data game : controversies in social science statistics
- The explanatory power of models : bridging the gap between empirical and theoretical research in the social sciences
- The general linear model : data analysis in the social and behavioral sciences
- The logic of causal order
- The multivariate social scientist : introductory statistics using generalized linear models
- The social sciences of quantification : from politics of large numbers to target-driven policies
- The statistical movement in early Victorian Britain : the foundation of empirical social research
- The theory and practice of item response theory
- The uncounted
- The uses and misuses of data and models : the mathematization of the human sciences
- Theory-based data analysis for the social sciences
- Time series analysis : regression techniques
- Time series analysis: univariate and multivariate methods
- Time series models for business and economic forecasting
- Time series models for business and economic forecasting
- Understanding and using advanced statistics
- Understanding quantitative history
- Understanding regression analysis : an introductory guide
- Understanding regression assumptions
- Understanding social statistics
- Understanding social statistics
- Understanding statistics for the social sciences with IBM SPSS
- Univariate tests for time series models
- Using IBM SPSS statistics for research methods and social science statistics
- Using Mplus for structural equation modeling : a researcher's guide
- Using R for data analysis in social sciences : a research project-oriented approach
- Using SPSS syntax : a beginner's guide
- Using and interpreting statistics in the social, behavioral, and health sciences
- Using statistics in the social and health sciences with SPSS and Excel
- What is quantitative longitudinal data analysis?
- What is quantitative longitudinal data analysis?
- Your statistical consultant : answers to your data analysis questions
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