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 Cursus: 202000332
 202000332Data Analysis II
 Cursus informatie
Cursus202000332
Studiepunten (ECTS)4
CursustypeOnderwijseenheid
VoertaalEngels
Contactpersoondr. W.A.C. Smink
E-mail-
Docenten
 Docent dr. S.M. van den Berg Contactpersoon van de cursus dr. W.A.C. Smink Docent dr. W.A.C. Smink Docent J. van Straalen - Pas
Collegejaar2020
Aanvangsblok
 2A
AanmeldingsprocedureZelf aanmelden via OSIRIS Student
Inschrijven via OSIRISJa
 Cursusdoelen
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } Students: Can recognize pre-post and other repeated measures designs (and distinguish within from between designs). Can make the decision when to enter a predictor variable as a fixed effect or a random effect. Can compute and interpret an intraclass correlation based on statistical output. Know how to use syntax to run a linear mixed model. Can interpret the output of a simple linear mixed model analysis for any within design, predict values, calculate confidence intervals and do hypothesis testing. Can report a simple linear mixed model analysis in APA format. Know when to use a nonparametric alternative for a linear mixed model. Know what nonparametric alternatives are available for linear mixed models. Know when to perform a logistic regression analysis, know how to do it, interpret and report the results APA style. Know how to compute probabilities from logoddsratios and vice versa.
 Inhoud
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } This Research Methods study unit in module 3 expands the linear model to the generalized linear mixed model. First we introduce linear mixed models and random effects. Departing from analyzing pre-post designs, we extend this to repeated measures analyses in general, including analysing mixed designs (within+between mixed designs). Students are familiarized with nonparametric alternatives tests: Friedmanâ€™s and Wilcoxonâ€™s test. Next, generalized linear models are introduced, but limited to analysing dichotomous outcome data through logistic regression. Great care is giving to choosing the right analysis and reshaping the data matrix appropriately. Through the entire course we will make active use of R and students will learn how to interpret the output properly  The interpretation of results and their generalization to populations are also emphasized. Students practise with APA-style reporting.
 Modulebeschrijving
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } This study unit is part of the module Cognition and Development (202000330). A module is offered as one educational unity and students take it as such.
 Participating study
 Bachelor Psychologie
 Module
 Module 3
Verplicht materiaal
Book
 Van den Berg (Editon 5) “Analyzing Data by Using Linear Models” (will be freely provided online)
Aanbevolen materiaal
-
Werkvormen
 Hoorcollege Vragenuur Werkcollege
Toetsen
 Written exam Handing in assignments
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