Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Book . 2022
License: CC BY SA
Data sources: ZENODO
https://doi.org/10.5507/ff.21....
Book . 2021 . Peer-reviewed
Data sources: Crossref
versions View all 2 versions
addClaim

Linear statistical models in psychology

Authors: Dostál, Daniel;

Linear statistical models in psychology

Abstract

Different kinds of linear regressions are useful in solving a wide range of problems encountered in psychology and other areas of empirical research. Procedures belonging to this family find their application in the processing of experimental data, in the analysis of questionnaire surveys and, for example, in the development of test norms. This text is intended for students who are familiar with the basic procedures of quantitative data analysis - descriptive statistics and statistical hypothesis testing. The aim of this textbook is to integrate and present this knowledge into the context of statistical modelling. The book describes both basic topics and specialized procedures of working with linear models. The reader is introduced to regression coefficients, indicators of model fit, handling nominal regressors and interaction terms. Several chapters are devoted to tests of statistical significance, construction of confidence bands, assumptions testing, and model diagnostics. Among more advanced techniques, the book covers the investigation of curvilinear dependencies, lognormal regression, stepwise and hierarchical regression, and mixed-effects models. The textbook also includes a set of data files for practicing the methods described.

Rozmanité druhy lineární regrese představují nástroj první volby při řešení širokého spektra problémů, na které narážíme v psychologii i dalších empirických vědách. Postupy spadající do této rodiny nachází své uplatnění při zpracování experimentálních dat, dotazníkových šetření nebo například při tvorbě testových norem. Tento text je určen studentům, kteří jsou seznámeni se základními postupy práce s kvantitativními daty - s popisnými statistikami a principem testování statistických hypotéz. Cílem těchto skript je tyto poznatky propojit a představit v kontextu statistického modelování. Skripta popisují základní témata i specializované postupy práce s lineárními modely. Čtenář je seznámen s regresními koeficienty, ukazateli kvality modelu, s prací s nominálními regresory i s interakčními členy. Několik kapitol je věnováno testům statistické významnosti, konstrukci pásů spolehlivosti, předpokladům užití lineárních modelů a diagnostice modelu. Z pokročilejších postupů text pokrývá zkoumání nelineárních závislostí, lognormální regresi, krokovou a hierarchickou regresi i modely se smíšenými efekty a další. Součástí skript je sada datových souborů k procvičování popisovaných metod.

Related Organizations
Keywords

quantitative data analysis, statistics, empirical research, psychology

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
Beta
sdg_colorsSDGs:
Related to Research communities