how to test the homogeneity of slopes by spss version 25

Generally, ANCOVA tries to demonstrate some effect by rejecting the null hypothesis thatĪll population means are equal when controlling for 1+ covariates.įor our example, this translates to “average posttreatment blood pressures are equal for all treaments when controlling for pretreatment blood pressure”. Surprisingly, analysis of covariance does not actually involve covariances as discussed in Covariance - Quick Introduction.īenefits of SPSS ANCOVA - Null Hypothesis

This analysis basically combines ANOVA with regression. This now becomes ANCOVA -short for analysis of covariance. We can do so by adding our pretest as a covariate to our ANOVA. We'd now like to examine the effect of medicine while controlling for pretreatment blood pressure. The relation between pretreatment and posttreatment blood pressure could be examined with simple linear regression because both variables are quantitative. This variable should therefore be taken into account as well. Now, posttreatment blood pressure is known to correlate strongly with pretreatment blood pressure. Our company wants to know if their medicine outperforms the other treatments: do these participants have lower blood pressures than the others after taking the new medicine? Since treatment is a nominal variable, this could be answered with a simple ANOVA. The data -partly shown below- are in blood-pressure.sav.

They tested their medicine against an old medicine, a placebo and a control group. SPSS ANCOVA Output - Between-Subjects EffectsĪ pharmaceutical company develops a new medicine against high blood pressure.

SPSS ANCOVA – Beginners Tutorial By Ruben Geert van den Berg under ANOVA & Statistics A-Z

How to test the homogeneity of slopes by spss version 25