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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 **University of Liverpool**.

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Social sciences -- Statistical methods
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**Social sciences -- Statistical methods**represents the subject, aboutness, idea or notion of resources found in**University of Liverpool**.- Label
- Social sciences -- Statistical methods

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- 100 statistical tests
- A beginner's guide to structural equation modeling
- A first course in Bayesian statistical methods
- A first course in structural equation modeling
- A guide for selecting statistical techniques for analyzing social science data
- A guide for selecting statistical techniques for analyzing social science data
- A handbook for data analysis in the behavioral sciences: methodological issues
- A handbook for data analysis in the behavioral sciences: statistical issues
- A mathematical primer for social statistics
- A mathematical primer for social statistics
- A primer of LISREL: basic applications and programming for confirmatory factor analytic models
- A primer on regression artifacts
- ANOVA : repeated measures
- ANOVA: repeated measures
- Advanced methods of data exploration and modelling
- Advanced quantitative data analysis
- Advances in factor analysis and structural equation models
- Advances in sequence analysis : theory, method, applications
- Agent-based models
- Agent-based models
- Aggregate data: analysis and interpretation
- Algunos problemas de formalizaciÃ³n y estimaciÃ³n en modelos de regresiÃ³n con variables cualitativas, aplicadas a la investigaciÃ³n social
- An easy guide to factor analysis
- An introduction to latent variable models
- Analysis of multivariate social science data
- Analysis of nominal data
- Analysis of ordinal data
- Analysis of ordinal data,[by] David K. Hildebrand, James D. Laing, Howard Rosenthal
- Analysis of qualitative data
- Analysis of qualitative data
- Analysis of variance
- Analysis of variance
- Analysis of variance
- Analytical urban geography: spatial patterns and trends
- Analyzing census microdata
- Analyzing census microdata
- Analyzing panel data
- Analyzing panel data
- Analyzing qualitative data
- Analyzing qualitative data
- Analyzing qualitative data
- Analyzing quantitative data : an introduction for social researchers
- Analyzing quantitative data : from description to explanation
- Analyzing single system design data
- Analyzing tabular data: loglinear and logistic models for social researchers
- Applied Bayesian forecasting and times series analysis
- Applied data-centric social sciences : concepts, data, computation, and theory
- Applied multiple regression/correlation analysis for the behavioral sciences
- Applied multivariate statistics for the social sciences
- Applied multivariate statistics for the social sciences
- Applied multivariate statistics for the social sciences
- Applied statistics for the social and health sciences
- Applied time series analysis for the social science
- Applied time series analysis for the social sciences
- Applying the Rasch model : fundamental measurement in the human sciences
- Arthur L. Bowley : a pioneer in modern statistics and economics
- Assessing inequality
- Assessing inequality
- Assessing the quality of survey data
- Basic statistics for business and economics
- Basic statistics for social research
- Basics of qualitative research : techniques and procedures for developing grounded theory
- Basics of qualitative research : techniques and procedures for developing grounded theory
- Basics of qualitative research: grounded theory procedures and techniques
- Basics of structural equation modeling
- Bayesian inference in the social sciences
- Beginning statistics : an introduction for social scientists
- Beginning statistics : an introduction for social scientists
- Behavioral statistics: logic and methods
- 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
- Business and economic statistics
- Canonical analysis and factor comparison
- Canonical analysis and factor comparison
- Categorical data analysis for the behavioral and social sciences
- Causal analysis with panel data
- Causal analysis with panel data
- Causal modeling
- Causal modeling
- Causal modeling
- Central tendency and variability
- Central tendency and variability
- Cluster analysis
- Cluster analysis
- Cluster analysis for social scientists
- Common problems, proper solutions: avoiding error in quantitative research
- Conceptualization and measurement in the social sciences
- Confidence intervals
- Confidence intervals
- Confirmatory factor analysis : a preface to LISREL
- Confirmatory factor analysis: a preface to LISREL
- Correlation and causality
- Critical statistics : seeing beyond the headlines
- Critical statistics : seeing beyond the headlines
- Data analysis : an introduction
- Data analysis : an introduction
- Data analysis and interpretation
- Data analysis for research designs : analysis of variance and multiple regression/correlation approaches
- Data analysis for the helping professions: a practical guide
- Data analysis for the social sciences : integrating theory and practice
- Data collection and analysis
- Data collection and analysis
- Data collection and analysis
- Data mining for the social sciences : an introduction
- Data theory and dimensional analysis
- Data theory and dimensional analysis
- Data, models and statistical analysis
- Dealing with statistics : what you need to know
- Demystifying social statistics
- Dependent data in social sciences research : forms, issues, and methods of analysis
- Design and analysis: a researcher's handbook
- Design and analysis: a researcher's handbook
- Design sensitivity: statistical power for experimental research
- Differential item functioning
- Differential item functioning
- Discriminant analysis
- Discriminant analysis
- Discriminant analysis
- Doing Grounded Theory : issues and discussions
- Doing secondary analysis
- Dynamic analysis in the social sciences
- Ecological inference
- Ecological inference
- Ecological inference : new methodological strategies
- Econometrics and data analysis for developing countries
- Essentials of research methods : a guide to social research
- Ethnostatistics : qualitative foundations for quantitative research
- Excel 2016 for social science statistics : a guide to solving practical problems
- Experiment design and statistical methods for behavioural and social research
- Experimental design and analysis
- 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
- Exploring data: an introduction to data analysis for social scientists
- Factfulness : ten reasons we're wrong about the world - and why things are better than you think
- Fixed effects regression models
- Fixed effects regression models
- Fractal analysis
- Fractal analysis
- Frontiers in massive data analysis
- Fundamentals of business statistics
- Fundamentals of business statistics
- Fundamentals of social statistics
- Handbook of data analysis
- Handbook of data analysis
- Handbook of data analysis
- Handbook of polytomous item response theory models
- Handbook of statistical modeling for the social and behavioral sciences
- Hierarchical linear models : applications and data analysis methods
- How to use SPSS syntax : an overview of common commands
- Indici statistici per analisi economiche e sociali
- 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
- Introducing data analysis for social scientists
- Introducing data analysis for social scientists
- Introducing multilevel modeling
- Introducing social statistics
- Introduction to applied Bayesian statistics and estimation for social scientists
- Introduction to business and economic statistics
- Introduction to casual analysis : exploring survey data by crosstabulation
- Introduction to causal analysis : exploring survey data by crosstabulation
- Introduction to mediation, moderation, and conditional process analysis : a regression-based approach
- Introduction to mediation, moderation, and conditional process analysis : a regression-based approach
- Introduction to quantitative research methods : an investigative approach
- Introduction to quantitative research methods : an investigative approach
- Introduction to social statistics
- Introduction to statistics: a non-parametric approach for the social sciences
- Introduction to survey sampling
- Introduction to survey sampling
- Introduction to time series analysis
- Introductory statistics for business and economics
- Introductory statistics for the behavioral sciences
- Introductory statistics for the behavioral sciences
- Invariant measurement : using Rasch models in the social, behavioral, and health sciences
- Just plain data analysis : finding, presenting, and interpreting social science data
- LISREL approaches to interaction effects in multiple regression
- LISREL approaches to interaction effects in multiple regression
- Latent growth curve modeling
- Latent growth curve modeling
- Linear statistical models and related methods: with applications to social research
- Linking and aligning scores and scales
- 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
- Making sense of multivariate data analysis
- Marginal models : for dependent, clustered, and longitudinal categorical data
- Marketing research with IBM SPSS statistics : a practical guide
- Mathematical methods in social science
- Mathematical-statistical models and qualitative theories for economic and social sciences
- Mathematics for social scientists
- Mathematics for social scientists
- Maximum likelihood estimation : logic and practice
- Maximum likelihood estimation: logic and practice
- Measurement in the social sciences: the link between theory and data
- Measuring the intentional world : realism, naturalism, and quantitative methods in the behavioral sciences
- Measuring the intentional world : realism, naturalism, and quantitative methods in the behavioral sciences
- Meta-analysis for public management and policy
- 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
- Methods of meta-analysis: correcting error and bias in research findings
- Modeling and interpreting interactive hypotheses in regression analysis
- Modeling data irregularities and structural complexities in data envelopment analysis
- Models for social networks with statistical applications
- Modern methods for robust regression
- Modern methods for robust regression
- Modern regression techniques using R : a practical guide for students and researchers
- 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
- Multiple and generalized nonparametric regression
- Multiple and generalized nonparametric regression
- Multiple comparisons
- Multiple indicators : an introduction
- Multiple indicators: an introduction
- Multiple regression in practice
- Multiple regression in practice
- Multivariate analysis for the biobehavioral and social sciences
- Multivariate general linear models
- Multivariate general linear models
- Multivariate statistics in the social sciences: a researcher's guide
- Multivariate tests for time series models
- New developments and techniques in structural equation modeling
- New developments in categorical data analysis for the social and behavioral sciences
- New developments in categorical data analysis for the social and behavioral sciences
- New developments in statistics for psychology and the social sciences
- New statistical procedures for the social sciences: modern solutions to basic problems
- Nonparametric and distribution-free methods for the social sciences
- Nonparametric measures of association
- Nonparametric measures of association
- Nonparametric statistics for the behavioral sciences
- Nonrecursive causal models
- Nonsampling error in social surveys
- Observing interaction : an introduction to sequential analysis
- Observing interaction : an introduction to sequential analysis
- Odds ratios in the analysis of contingency tables
- Ordinal measurement in the behavioral sciences
- PDQ statistics
- Path analysis: a primer
- Peripheralization : the making of spatial dependencies and social injustice
- Polytomous item response theory models
- Practical statistics for students: an introductory text
- Probability and social science : methodological relationships between the two approaches
- Q methodology
- Q methodology
- Q methodology
- Qualitative analysis for social scientists
- Qualitative data analysis : practical strategies
- Qualitative research : methods in the social sciences
- Quantile regression
- Quantile regression
- Quantitative research : methods in the social sciences
- Random factors in ANOVA
- Random factors in ANOVA
- Rasch models for measurement
- Rasch models for measurement
- Regression analysis : a constructive critique
- Regression diagnostics
- Regression diagnostics
- Regression models: censored, sample-selected or truncated data
- Regression with dummy variables
- Regression with dummy variables
- Reliability and validity assessment
- Reliability and validity assessment
- Reliability for the social sciences: theory and applications
- Research design : qualitative and quantitative approaches
- Research design : qualitative, quantitative & mixed methods approaches
- Research design : qualitative, quantitative, and mixed methods approaches
- Research design in social research
- Researching developing countries : a data resource guide for social scientists
- SAGE research methods
- SAGE secondary data analysis
- SPSS for social scientists
- SPSS: statistical package for the social sciences
- Sampling theory : for the ecological and natural resource sciences
- Science outside the laboratory : measurement in field science and economics
- Secondary analysis of survey data
- Secondary analysis of survey data
- Simple statistics: a course book for the social sciences
- Social and economic statistics for Africa: their sources, collection, uses and reliability
- Social measurement
- Social measurement and social indicators: issues of policy and theory
- Social statistics
- Social statistics
- Social statistics
- Social statistics
- Sorting data : collection and analysis
- Spline regression models
- Spline regression models
- Starting statistics : a short, clear guide
- Statistical Games and Human Affairs : This View from Within
- Statistical analysis quick reference guidebook : with SPSS examples
- Statistical applications for the behavioral sciences
- Statistical games and human affairs: the view from within
- Statistical methods for meta-analysis
- Statistical methods for social scientists
- Statistical methods for the social sciences
- Statistical methods for the social sciences
- Statistical methods for validation of assessment scale data in counseling and related fields
- Statistical methods in social science research
- Statistical modeling and analysis for complex data problems
- Statistical modeling and analysis for complex data problems
- 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 for the behavioral sciences
- Statistical power analysis with missing data : a structural equation modeling approach
- Statistical reasoning for the behavioral sciences
- Statistical thinking: a structural approach
- Statistics
- Statistics and data interpretation for social work
- Statistics and society : data collection and interpretation
- Statistics for business and economics
- Statistics for business and economics
- Statistics for business and economics: methods and applications
- Statistics for students in behavioral sciences
- Statistics for the behavioral sciences
- Statistics for the helping professions
- Statistics for the social and behavioral sciences
- Statistics for the social sciences
- Statistics for the social sciences
- Statistics for the social sciences: with computer applications
- Statistics in society : the arithmetic of politics
- Statistics workbook for social science students
- Structural equation modeling : foundations and extensions
- Structural equation modeling with LISREL, PRELIS, and SIMPLIS : basic concepts, applications, and programming
- Structural equation modeling with LISREL: essentials and advances
- Structural equation modeling with Mplus : basic concepts, applications, and programming
- Structural equations with latent variables
- Structural equations with latent variables
- Survey sampling and multivariate analysis for social scientists and engineers
- Systematic reviews in the social sciences : a practical guide
- Systematic reviews in the social sciences : a practical guide
- Taxonomy and behavioral science: comparative performance of grouping methods
- Test anxiety : applied research, assessment, and treatment interventions
- Test item bias
- Test item bias
- Tests of significance
- The SAGE handbook of measurement
- The SAGE handbook of quantitative methodology for the social sciences
- The analysis and interpretation of multivariate data for social scientists
- The dimensions of quantitative research in history
- The logic of causal order
- The logic of causal order
- The multivariate social scientist : introductory statistics using generalized linear models
- The multivariate social scientist : introductory statistics using generalized linear models
- The reviewer's guide to quantitative methods in the social sciences
- The social index: a new technique for measuring social trends
- The social sciences of quantification : from politics of large numbers to target-driven policies
- 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: regression techniques
- Understanding and evaluating research in applied and clinical settings
- Understanding and evaluating research in applied clinical settings
- Understanding and using advanced statistics
- Understanding and using advanced statistics
- Understanding data
- Understanding data
- Understanding data
- Understanding quantitative history
- Understanding regression analysis : an introductory guide
- Understanding regression analysis : an introductory guide
- Understanding regression analysis: an introductory guide
- Understanding regression assumptions
- Understanding regression assumptions
- Understanding significance testing
- Understanding social statistics
- Understanding social statistics
- Understanding social statistics
- Understanding statistics : an introduction for the social sciences
- Univariate tests for time series models
- Univariate tests for time series models
- 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 SPSS syntax : a beginner's guide
- Using statistics in social research : a concise approach
- Validity and validation
- Validity and validation
- What is quantitative longitudinal data analysis?
- Working with statistics: an introduction to quantitative methods for social scientists
- Your statistical consultant : answers to your data analysis questions

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