If the stat text says that a signifcant omnibus ANOVA is a prerequisite for HSD, it is high time to adopt a different stats text! Cheers, Karl W.
________________________________ From: Rick Froman [mailto:[EMAIL PROTECTED] Sent: Tuesday, April 03, 2007 11:40 PM To: Teaching in the Psychological Sciences (TIPS) Subject: RE: [tips] Re: ANOVA interpretation Here's the thing: this isn't a research project but the results of a homework problem. More specifically, it is the result of a mistake in data entry (since no stats text author would likely ever produce such a result on purpose when the text says that a significant omnibus F-test is a prerequisite for HSD). So there is nothing meaningful to be gained by trying to determine what might be logically expected in this case. I assume the data is constructed. My interest was more in the fact that it was theoretically possible to have a significant F test and no significant HSD comparisons. Rick Dr. Rick Froman Psychology Department Box 3055 John Brown University Siloam Springs, AR 72761 (479) 524-7295 [EMAIL PROTECTED] "Pete, it's a fool that looks for logic in the chambers of the human heart" - Ulysses Everett McGill ________________________________ From: Jim Clark [mailto:[EMAIL PROTECTED] Sent: Tue 4/3/2007 7:42 PM To: Teaching in the Psychological Sciences (TIPS) Subject: [tips] Re: ANOVA interpretation Hi As shown in following example, significant omnibus and nonsignificant Tukeys is not strictly speaking a simple product of small sample size (the 4 groups below each have 90 subjects). It also depends on magnitude of difference relative to variation within groups (MSE) and the specific pattern of the difference. Below, groups 1 and 2 are different than groups 3 and 4 IN THE POPULATION. Although maximum difference is almost significant by Tukey (p = .055) that really does not capture the pattern in the data, as shown by the subsequent contrast analysis. The contrast between 1&2 vs 3&4 is highly significant (p = .008). The lesson, analyses for predicted patterns in data are more sensitive than omnibus or post hoc analyses (as long as the predicted pattern is in fact observed in the data, of course). Rick should post a description of the conditions for the factor (WITHOUT MEANS) to see if we could agree on a predicted pattern that could be tested by a single df contrast. Take care Jim set seed = 435678234. input program. loop o = 1 to 360. end case. end loop. end file. end input program. comp group = trunc((o-1)/90)+1. comp dep = rnd(rv.norm(50,10.5)). if group > 2 dep = dep + 5. glm dep by group /posthoc = group(tukey). Tests of Between-Subjects Effects Dependent Variable: dep Source Type III Sum of df Mean Square F Sig. Squares Corrected Model 1027.744(a) 3 342.581 2.687 .046 Intercept 990360.900 1 990360.900 7767.647 .000 group 1027.744 3 342.581 2.687 .046 Error 45389.356 356 127.498 Total 1036778.000 360 Corrected Total 46417.100 359 a R Squared = .022 (Adjusted R Squared = .014) Post Hoc Tests group Multiple Comparisons Dependent Variable: dep Tukey HSD (I) (J) Mean Difference Std. Sig. 95% Confidence Interval group group (I-J) Error Lower Bound Upper Bound 1.000 2.000 -1.43333 1.683239 .830 -5.77812 2.91145 3.000 -4.27778 1.683239 .055 -8.62256 .06701 4.000 -3.51111 1.683239 .160 -7.85590 .83368 2.000 3.000 -2.84444 1.683239 .331 -7.18923 1.50034 4.000 -2.07778 1.683239 .605 -6.42256 2.26701 3.000 4.000 .76667 1.683239 .969 -3.57812 5.11145 Homogeneous Subsets Tukey HSD group N Subset 1 1.000 90 50.14444 2.000 90 51.57778 4.000 90 53.65556 3.000 90 54.42222 Sig. .055 glm dep by group /contr(group) = spec(-1 -1 1 1 -1 1 0 0 0 0 -1 1). Source Type III Sum of df Mean Square F Sig. Squares Corrected Model 1027.744(a) 3 342.581 2.687 .046 Intercept 990360.900 1 990360.900 7767.647 .000 group 1027.744 3 342.581 2.687 .046 Error 45389.356 356 127.498 Total 1036778.000 360 Corrected Total 46417.100 359 Custom Hypothesis Tests group Special Dependent Contrast Variable dep L1 Contrast Estimate 6.356 Std. Error 2.380 Sig. .008 L2 Contrast Estimate 1.433 Std. Error 1.683 Sig. .395 L3 Contrast Estimate -.767 Std. Error 1.683 Sig. .649 James M. Clark Professor of Psychology 204-786-9757 204-774-4134 Fax [EMAIL PROTECTED] --- To make changes to your subscription go to: http://acsun.frostburg.edu/cgi-bin/lyris.pl?enter=tips&text_mode=0&lang= english <http://acsun.frostburg.edu/cgi-bin/lyris.pl?enter=tips&text_mode=0<=eng lish> --- To make changes to your subscription go to: http://acsun.frostburg.edu/cgi-bin/lyris.pl?enter=tips&text_mode=0&lang=english
