Inhoudsopgave
Chapter 4 The IBM SPSS statistics environment...................................................2
4.10 The syntax editor......................................................................................................... 2
Chapter 6 The beast of bias................................................................................3
6.2 What is bias?.................................................................................................................. 3
6.3 Outliers.......................................................................................................................... 3
6.4 Overview of assumptions............................................................................................... 4
6.5 Additivity and linearity................................................................................................... 4
6.6 Normally distributed something or other.......................................................................4
6.7 Homoscedasticity/homogeneity of variance...................................................................4
6.8 Independence................................................................................................................ 5
6.9 Spotting outliers............................................................................................................. 5
6.10 Spotting normality....................................................................................................... 5
6.11 Spotting linearity and heteroscedasticity/heterogeneity of variance...........................5
6.12 Reducing bias............................................................................................................... 6
Chapter 9 The linear model (regression)..............................................................6
9.2 An introduction to the linear model (regression)............................................................6
9.6 Fitting linear models: the general procedure.................................................................8
9.7 Using SPSS statistics to fit a linear model with one predictor.........................................9
9.9 The linear model with two or more predictors (multiple regression)..............................9
9.10 Using SPSS statistics to fit a linear model with several predictors...............................9
Chapter 10 Comparing two means.....................................................................11
10.2 Looking at differences................................................................................................ 11
10.4 Categorical predictors in the linear model.................................................................11
10.5 The t-test................................................................................................................... 12
10.6 Assumptions of the t-test...........................................................................................12
10.7 Comparing two means: general procedure................................................................12
10.8 Comparing two independent means using SPSS Statistics.........................................12
Chapter 11 Moderation, mediation and multicategory predictors........................13
11.2 The PROCESS tool...................................................................................................... 13
11.3 Moderation: interactions in the linear model..............................................................13
, 11.4 Mediation................................................................................................................... 14
11.5 Categorical predictors in regression...........................................................................14
Chapter 12 GLM 1: Comparing several independent means.................................15
12.2 Using a linear model to compare several means........................................................15
12.3 Assumptions when comparing means........................................................................16
12.6 General procedure of one-way ANOVA.......................................................................17
Chapter 13 GLM 2: Comparing means adjusted for other predictors....................17
13.2 What is ANCOVA?....................................................................................................... 17
13.4 Assumptions and issues in ANCOVA...........................................................................17
13.5 Conducting ANCOVA using SPSS statistics.................................................................18
13.6 Interpreting ANCOVA.................................................................................................. 19
13.7 Testing the assumptions of homogeneity of regression slopes...................................19
Chapter 18 Exploratory factor analysis..............................................................20
18.2 When to use factor analysis.......................................................................................20
18.3 Factors and components............................................................................................20
18.4 Discovering factors.................................................................................................... 21
18.5 An anxious example................................................................................................... 21
18.6 Factor analysis using SPSS statistics..........................................................................22
18.10 Reliability analysis using SPSS statistics..................................................................22
Chapter 20 Categorical outcomes: logistic regression.........................................23
20.2 What is logistic regression?........................................................................................ 23
20.4 Sources of bias and common problems......................................................................24
20.5 Binary logistic regression........................................................................................... 24
20.7 Reporting logistic regression......................................................................................25
Chapter 4 The IBM SPSS statistics environment
4.10 The syntax editor
Using syntax creates a record of your analysis and makes it reproducible, which is an
important part of engaging in open science practices.
To open a syntax editor window:
- File > new > syntax
, The easiest way to generate syntax in the beginning is to use dialog boxes to specify the
analysis you want to do and then click > paste
You can run the syntax a command at a time from either the current command (Run >
step through > from current) or the beginning (run > step through > from start)
Chapter 6 The beast of bias
6.2 What is bias?
Bias: the summary statistics that we estimate can be at odds with the true values
Models will not predict the outcome perfectly, so for each observation there is some amount of
error.
6.3 Outliers
Outlier: a score very different from the rest of the data
Chapter 4 The IBM SPSS statistics environment...................................................2
4.10 The syntax editor......................................................................................................... 2
Chapter 6 The beast of bias................................................................................3
6.2 What is bias?.................................................................................................................. 3
6.3 Outliers.......................................................................................................................... 3
6.4 Overview of assumptions............................................................................................... 4
6.5 Additivity and linearity................................................................................................... 4
6.6 Normally distributed something or other.......................................................................4
6.7 Homoscedasticity/homogeneity of variance...................................................................4
6.8 Independence................................................................................................................ 5
6.9 Spotting outliers............................................................................................................. 5
6.10 Spotting normality....................................................................................................... 5
6.11 Spotting linearity and heteroscedasticity/heterogeneity of variance...........................5
6.12 Reducing bias............................................................................................................... 6
Chapter 9 The linear model (regression)..............................................................6
9.2 An introduction to the linear model (regression)............................................................6
9.6 Fitting linear models: the general procedure.................................................................8
9.7 Using SPSS statistics to fit a linear model with one predictor.........................................9
9.9 The linear model with two or more predictors (multiple regression)..............................9
9.10 Using SPSS statistics to fit a linear model with several predictors...............................9
Chapter 10 Comparing two means.....................................................................11
10.2 Looking at differences................................................................................................ 11
10.4 Categorical predictors in the linear model.................................................................11
10.5 The t-test................................................................................................................... 12
10.6 Assumptions of the t-test...........................................................................................12
10.7 Comparing two means: general procedure................................................................12
10.8 Comparing two independent means using SPSS Statistics.........................................12
Chapter 11 Moderation, mediation and multicategory predictors........................13
11.2 The PROCESS tool...................................................................................................... 13
11.3 Moderation: interactions in the linear model..............................................................13
, 11.4 Mediation................................................................................................................... 14
11.5 Categorical predictors in regression...........................................................................14
Chapter 12 GLM 1: Comparing several independent means.................................15
12.2 Using a linear model to compare several means........................................................15
12.3 Assumptions when comparing means........................................................................16
12.6 General procedure of one-way ANOVA.......................................................................17
Chapter 13 GLM 2: Comparing means adjusted for other predictors....................17
13.2 What is ANCOVA?....................................................................................................... 17
13.4 Assumptions and issues in ANCOVA...........................................................................17
13.5 Conducting ANCOVA using SPSS statistics.................................................................18
13.6 Interpreting ANCOVA.................................................................................................. 19
13.7 Testing the assumptions of homogeneity of regression slopes...................................19
Chapter 18 Exploratory factor analysis..............................................................20
18.2 When to use factor analysis.......................................................................................20
18.3 Factors and components............................................................................................20
18.4 Discovering factors.................................................................................................... 21
18.5 An anxious example................................................................................................... 21
18.6 Factor analysis using SPSS statistics..........................................................................22
18.10 Reliability analysis using SPSS statistics..................................................................22
Chapter 20 Categorical outcomes: logistic regression.........................................23
20.2 What is logistic regression?........................................................................................ 23
20.4 Sources of bias and common problems......................................................................24
20.5 Binary logistic regression........................................................................................... 24
20.7 Reporting logistic regression......................................................................................25
Chapter 4 The IBM SPSS statistics environment
4.10 The syntax editor
Using syntax creates a record of your analysis and makes it reproducible, which is an
important part of engaging in open science practices.
To open a syntax editor window:
- File > new > syntax
, The easiest way to generate syntax in the beginning is to use dialog boxes to specify the
analysis you want to do and then click > paste
You can run the syntax a command at a time from either the current command (Run >
step through > from current) or the beginning (run > step through > from start)
Chapter 6 The beast of bias
6.2 What is bias?
Bias: the summary statistics that we estimate can be at odds with the true values
Models will not predict the outcome perfectly, so for each observation there is some amount of
error.
6.3 Outliers
Outlier: a score very different from the rest of the data
