Analyzing data using spss glm procedure |Statistics
This lab asks you to analyze a simple matched-groups design in two ways: using the dependent groups t test, and analyzing the same data as a randomized blocks design with p=2 levels of the within-subjects factor (using SPSS’s GLM procedure).
In this study, the researcher is studying the effect of participation in an afterschool program on problem behaviors (e.g. smoking, risky sex) in teens. Because participants in the program are volunteers, rather than being randomly assigned to conditions, the group of participating teens differs in a number of ways from non-participants most importantly in a composite measure of “social/academic risk.” The researcher decides to try to control for group differences by matching pairs of students, one participant with one non-participant, with similar risk scores. Fifteen matched pairs of students are created, so the total number of students followed is N=30. After three months of program, the scores of participants and non-participants are compared (the dependent variable is a composite measure of problem behaviors, Y, obtained by summing severity measures across a set of target behaviors).
DATA:
Pair | Partic | Non-Partic |
01 | 16 | 22 |
02 | 09 | 14 |
03 | 18 | 14 |
04 | 23 | 26 |
05 | 07 | 19 |
06 | 22 | 16 |
07 | 14 | 17 |
08 | 09 | 17 |
09 | 14 | 09 |
10 | 16 | 25 |
11 | 15 | 15 |
12 | 17 | 23 |
13 | 25 | 26 |
14 | 09 | 18 |
15 | 17 | 12 |
Type the above data into the SPSS Data Editor window, or save this file as an unformatted text file and write SPSS syntax to read it in.