College aantekeningen Advanced Research Methods And Statistics Clinical Psychology () Discovering Statistics Using IBM SPSS Statistics, ISBN: 9781526422965

ARMS

HC1

- Simple linear regression: 1 outcome and 1 predictor



- Multiple linear regression: involves 1 outcome and multiple predictors




Relevance of a predictor (1)

1. The amount of variance explained (R2) i.e. the sizes of the residuals




2. The slope of the regression line (B1), als X 1 punt stijgt, wat gebeurt er dan met Y?




Multiple linear regression (MLR)

- All assumptions (FIND IN GRASPLE, WILL BE ON TEST)

, - The model: ^y=predicted, Y1=0bserved. Observed score = predicted score + residual




- Types of variables
 Distinction between 4 measurement levels: nominal, ordinal (both categorical), interval,
ratio (quantitative or numerical)
 MLR requires continiour outcome and continuous predictors
 Categorical predictors can be included if changed to dummy variable (gender: male=1,
female=0 for example). (1 & 2 not allowed, only 0 and 1 is allowed




(dummycoding kan worden geoefend op grasple)

C. MLR and hierarchical MLR

Hierarchical MLR example:
Are social network factors (as measured by child support (X3) and spouse support (X4) improving the
prediction of Life Satisfaction, if the effect of age and years of education are already accounted for?

 Model 1: alleen Age en years of education


 Model 2: age, years of education met daarbij spouse support en child support