Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Mathematical statistics --- Psychology --- Psychometrics --- Discriminant analysis --- Psychometrics. --- Discriminant analysis. --- #SBIB:303H520 --- Analysis, Discriminant --- Classification theory (Statistics) --- Discrimination theory (Statistics) --- Multivariate analysis --- Measurement, Mental --- Measurement, Psychological --- Psychological measurement --- Psychological scaling --- Psychological statistics --- Psychometry (Psychophysics) --- Scaling, Psychological --- Psychological tests --- Scaling (Social sciences) --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Measurement --- Scaling --- Methodology

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Quantitative methods in social research --- Mathematical statistics --- Social sciences --- -Social sciences --- -#SBIB:303H520 --- #SBIB:001.AANKOOP --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Statistical methods --- Research --- -Longitudinal studies --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Longitudinal studies. --- Statistical methods. --- #SBIB:303H520 --- Longitudinal studies

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This volume presents contributions on handling data in which the postulate of independence in the data matrix is violated. When this postulate is violated and when the methods assuming independence are still applied, the estimated parameters are likely to be biased, and statistical decisions are very likely to be incorrect. Problems associated with dependence in data have been known for a long time, and led to the development of tailored methods for the analysis of dependent data in various areas of statistical analysis. These methods include, for example, methods for the analysis of longitudinal data, corrections for dependency, and corrections for degrees of freedom. This volume contains the following five sections: growth curve modeling, directional dependence, dyadic data modeling, item response modeling (IRT), and other methods for the analysis of dependent data (e.g., approaches for modeling cross-section dependence, multidimensional scaling techniques, and mixed models). Researchers and graduate students in the social and behavioral sciences, education, econometrics, and medicine will find this up-to-date overview of modern statistical approaches for dealing with problems related to dependent data particularly useful.

Social sciences --- Statistical methods. --- Research --- Methodology. --- Statistics. --- Psychometrics. --- Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. --- Statistical Theory and Methods. --- Mathematical statistics. --- Statistics for Social Sciences, Humanities, Law. --- Measurement, Mental --- Measurement, Psychological --- Psychological measurement --- Psychological scaling --- Psychological statistics --- Psychology --- Psychometry (Psychophysics) --- Scaling, Psychological --- Psychological tests --- Scaling (Social sciences) --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Measurement --- Scaling --- Methodology --- Statistics .

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This volume presents contributions on handling data in which the postulate of independence in the data matrix is violated. When this postulate is violated and when the methods assuming independence are still applied, the estimated parameters are likely to be biased, and statistical decisions are very likely to be incorrect. Problems associated with dependence in data have been known for a long time, and led to the development of tailored methods for the analysis of dependent data in various areas of statistical analysis. These methods include, for example, methods for the analysis of longitudinal data, corrections for dependency, and corrections for degrees of freedom. This volume contains the following five sections: growth curve modeling, directional dependence, dyadic data modeling, item response modeling (IRT), and other methods for the analysis of dependent data (e.g., approaches for modeling cross-section dependence, multidimensional scaling techniques, and mixed models). Researchers and graduate students in the social and behavioral sciences, education, econometrics, and medicine will find this up-to-date overview of modern statistical approaches for dealing with problems related to dependent data particularly useful.

Psychology --- Sociology --- Statistical science --- Law --- Mathematical statistics --- psychologie --- wetgeving --- statistiek --- statistisch onderzoek

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Psychology --- Statistical science --- psychologie --- statistiek --- statistisch onderzoek --- Discriminant analysis. --- Psychometrics. --- Measurement, Mental --- Measurement, Psychological --- Psychological measurement --- Psychological scaling --- Psychological statistics --- Psychometry (Psychophysics) --- Scaling, Psychological --- Psychological tests --- Scaling (Social sciences) --- Analysis, Discriminant --- Classification theory (Statistics) --- Discrimination theory (Statistics) --- Multivariate analysis --- Measurement --- Scaling --- Methodology --- Psicometria --- Anàlisi discriminant --- Teoria de la classificació (Estadística) --- Teoria de la discriminació (Estadística) --- Anàlisi multivariable --- Escales psicològiques --- Mesuraments mentals --- Mesuraments psicològics --- Escales (Ciències socials) --- Psicofisiologia --- Anàlisi factorial --- Escala multidimensional --- Metaanàlisi --- Tests i proves en educació --- Psicofísica --- Tests psicològics