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Compact overzicht SPSS vaardighedentoets
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Vanuit grasple de belangrijkste stappen om de SPSS vaardighedentoets te kunnen halen.
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SPSS VaardighedenTechniek SPSS-hoofdstap Deelstappen
Multipele Analyze > Uitschieters = Save > standarized residuals (Y)-3/3 (normaal), Mahalanobis (X) <10 +
regressie regression > 2 (# onafhankelijke variabelen) en Cook’s distances (XY) <1 (normaal)
Lineair Homoscedasticiteit = Plots > ZPRED (X) en ZRESID (Y)
Multicollineariteit = Statistics > Collinearity Diagnostics (tolerance <0.2 en VIF >10)
Normaal verdeeld = Plots > histogram
Hiërarchische regressie = Next en Statistics > R sqaured change
Tweeweg Analyze > GLM > Groepsvariabelen = fixed factors
ANOVA univariate Gemiddeldendiagram = Profile Plots > horizontal axis (>levels) > seperate lines (<)
Homoscedasticiteit = Options > homogenity test (Levene)
Effectgrootte = Options > estimates of effect (partial η2)
Paarsgewijze vergelijkingen = Post-Hoc (factor >2 levels) > Bonferroni correctie
Descriptieve statistieken = Options > descriptive statistics
ANOVA als MR = Options > parameter estimates (B-coëfficiënten)
Interactie-effect interpreteren via gemiddeldiagram (plots) of test van simpele
hoofeffecten (via SYNTAX > tabel pairwise comparisons)
ANCOVA Analyze > GLM > Groepsvariabelen = fixed factors
univariate Model aanmaken (interactie toetsen) = Model > Build terms > Covariaat * Factor
Geen interactie = Reset > normale ANCOVA uitvoeren
Plot = Plots > horizontal axis (groepsvariabele) > add
Paarsgewijze vergelijkingen = EM Means > factor > Display means for > compare
main effects > Confidence interval (Boneferroni)
Descriptieve statistieken = Options > descriptive statistics (ongecorrigeerd)
Effectgrootte = Options > estimates of effect (partial η2)
Homoscedasticiteit = Options > homogenity test (Levene)
ANCOVA als MR = Options > parameter estimates (B-coëfficiënten)
Diagram = Graphs > Chart Builder > Scatter/Dot > Grouped Scatter > groepsvariabele
in set color > elements > fit line at subgroups
HM Analyze > GLM > Binnensubject factor benoemen = factor 1 (naam) > levels (add) > define (?)1, (?)2
ANOVA Repeated Diagram = Plots > factor tijd (hor) + add
measures Paarsgewijs = EM-means > display main effects for (factor) > compare main effects >
Bonneferoni
Descriptieve statistieken = Options > descriptive statistics
Effectgrootte = Options > estimates of effect
Nog een subjectfactor = nogmaals doorlopen en bij Plots (lines = andere factor).
Interactie-effect interpreteren via gemiddeldiagram (plots) of test van simpele
hoofeffecten (via SYNTAX > tabel pairwise comparisons).
MD Analyze > GLM > Diagram = Plots > horizontaal (within) en aparte lijnen (between)
ANOVA Repeated Descriptieve statistieken = Options > descriptive statistics
measures Effectgrootte = Options > estimates of effect > parameter estimates
Homoscedasticiteit = Options > homogenity test (Levene)
Paarsgewijs = binnensubject =EM-means > display main effects for (factor) >
compare main effects > Bonneferoni OF tussensubject = Post-Hoc (minimaal 3 levels)
Moderatie Analyze > Centreren SPSS = Transform > Compute Variable > Variabele – Gemiddelde (alleen
(MR) regression > punten gebruiken).
Lineair Interactieterm SPSS = Transform > Compute Variable > interactie-term
Daarna MR = 3 termen invoegen
Interactie-effect bepalen = visualiseren of uitschrijven regressievergelijking
Moderatie Analyze > Moderator = W > model number > 1 (CI 95, bootstrap 5000)
(Process) Regression > Options = Generate code for visualizing interactions + Mean center for construction
PROCESS of products (all variables that define products). Probe-interactions > if p <0.05,
conditioning values -1SD, mean, +1SD. W = interval = Johnson-Neyman output.
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