Question

Can someone please USE SPSS and show me their analysis?

A behavior analyst would like to evaluate the effectiveness of a new technique for controlling classroom outbursts of unruly children. For a sample of n=4 children the number of outbursts is recorded 1 day before treatment and again 1 week, 1 month and 6 months after treatment. The data are as follows:

Child --Before-- 1 week --1 month-- 6 months

A --8 --2-- 1-- 1

B-- 4 --1 --1 --0

C--6-- 2-- 0-- 2

D-- 8-- 3 --4 --1

Use a repeated measures ANOVA with alpha = .05 to determine whether there are significant changes in behavior over time (write all the steps involved in testing the hypothesis). Use SPSS to solve this problem. Please make sure to show all the steps of hypothesis testing.

Answer 1

Result:

Can someone please USE SPSS and show me their analysis?

A behavior analyst would like to evaluate the effectiveness of a new technique for controlling classroom outbursts of unruly children. For a sample of n=4 children the number of outbursts is recorded 1 day before treatment and again 1 week, 1 month and 6 months after treatment. The data are as follows:

Child --Before-- 1 week --1 month-- 6 months

A --8 --2-- 1-- 1

B-- 4 --1 --1 --0

C--6-- 2-- 0-- 2

D-- 8-- 3 --4 --1

Use a repeated measures ANOVA with alpha = .05 to determine whether there are significant changes in behavior over time (write all the steps involved in testing the hypothesis). Use SPSS to solve this problem. Please make sure to show all the steps of hypothesis testing.

Ho: There is no changes in behavior over time

H1: There is a changes in behavior over time

Calculated F= 21.000, P=0.000 which is less than 0.05 level. Ho is rejected.

We conclude that there is significant changes in behavior over time.

Enter the data in 4 columns

v1	v2	v3	v4
8	2	1	1
4	1	1	0
6	2	0	2
8	3	4	1

In menu select Analyze, General Linear Model, Repeated Measures enter number of levels as 4 and define the 4 variables as 4 factors.

OR

Spss syntax

GLM v1 v2 v3 v4

/WSFACTOR=factor1 4 Polynomial

/METHOD=SSTYPE(3)

/PRINT=DESCRIPTIVE

/CRITERIA=ALPHA(.05)

/WSDESIGN=factor1.

Spss output:

General Linear Model

[DataSet0]

Within-Subjects Factors
Measure:   MEASURE_1
factor1	Dependent Variable
1	v1
2	v2
3	v3
4	v4

Descriptive Statistics
	Mean	Std. Deviation	N
v1	6.5000	1.91485	4
v2	2.0000	.81650	4
v3	1.5000	1.73205	4
v4	1.0000	.81650	4

Multivariate Tests
Effect		Value	F	Hypothesis df	Error df	Sig.
factor1	Pillai's Trace	.948	18.062	2.000	2.000	.052
	Wilks' Lambda	.052	18.062	2.000	2.000	.052
	Hotelling's Trace	18.062	18.062	2.000	2.000	.052
	Roy's Largest Root	18.062	18.062	2.000	2.000	.052

Mauchly's Test of Sphericity
Measure:   MEASURE_1
Within Subjects Effect	Mauchly's W	Approx. Chi-Square	df	Sig.	Epsilon
					Greenhouse-Geisser	Huynh-Feldt	Lower-bound
factor1	.000	.	5	.	.640	1.000	.333

Tests of Within-Subjects Effects
Measure:   MEASURE_1
Source		Type III Sum of Squares	df	Mean Square	F	Sig.
factor1	Sphericity Assumed	77.000	3	25.667	21.000	.000
	Greenhouse-Geisser	77.000	1.921	40.091	21.000	.002
	Huynh-Feldt	77.000	3.000	25.667	21.000	.000
	Lower-bound	77.000	1.000	77.000	21.000	.020
Error(factor1)	Sphericity Assumed	11.000	9	1.222
	Greenhouse-Geisser	11.000	5.762	1.909
	Huynh-Feldt	11.000	9.000	1.222
	Lower-bound	11.000	3.000	3.667

Tests of Within-Subjects Contrasts
Measure:   MEASURE_1
Source	factor1	Type III Sum of Squares	df	Mean Square	F	Sig.
factor1	Linear	57.800	1	57.800	51.000	.006
	Quadratic	16.000	1	16.000	12.000	.041
	Cubic	3.200	1	3.200	2.667	.201
Error(factor1)	Linear	3.400	3	1.133
	Quadratic	4.000	3	1.333
	Cubic	3.600	3	1.200

Tests of Between-Subjects Effects
Measure:   MEASURE_1
Transformed Variable:   Average
Source	Type III Sum of Squares	df	Mean Square	F	Sig.
Intercept	121.000	1	121.000	27.923	.013
Error	13.000	3	4.333