Re: [ECOLOG-L] planned contrasts replacing 2-way ANOVA
Orthogonal sets of a priori contrasts do not require adjustment of p-values because they ARE simply components of the ANOVA. That is why they are so powerful for hypothesis testing. They are also greatly under utilized. William J. Resetarits Program Director Population and Community Ecology Cluster Division of Environmental Biology National Science Foundation 4201 Wilson Blvd., Suite 635 wrese...@nsf.gov Voice (703) 292-7184 Fax (703) 292-9064 -Original Message- From: Ecological Society of America: grants, jobs, news on behalf of Asaf Sadeh Sent: Wed 7/7/2010 11:20 AM To: ECOLOG-L@LISTSERV.UMD.EDU Subject: [ECOLOG-L] planned contrasts replacing 2-way ANOVA I am planning a 2x2 factorial experiment whe Dear list members, I am planning a 2x2 factorial experiment where I record several response variables to test several hypotheses. Some of these hypotheses can be tested using the usual 2-way ANOVA. That is, the significance or non significance of the two main effects and their interaction is expected to provide sufficient information to draw conclusions regarding these hypotheses. However, another hypothesis focuses on one of the four treatment combinations, and would be best approached by comparing this focal treatment with the other three. However, if I use the 2-way ANOVA, some possible results may be inconclusive, and require further "post hoc" analyses with a reduced threshold for significance. Since my a-priori hypothesis calls for 3 specific contrasts, it makes statistical sense to me that I can skip the 2-way ANOVA and only perform these 3 contrasts without reducing the significance threshold. The logic behind this is that these 3 planned contrasts replace the 3 component tests of the 2-way ANOVA procedure (2 for the main effects and one for their interaction) that are each always done without any change to the significance threshold. Though I have found support for this approach on online statistics lectures notes, I have never seen it taken in any published study, and I wonder if it is indeed kosher (and if it can be expected to pass reviewers). I would highly appreciate input on this, and especially references to back this approach in case it is valid. Thank you very much, Asaf
Re: [ECOLOG-L] planned contrasts replacing 2-way ANOVA
There should be no problem with using a priori contrasts. No adjustment of the p-value is required, UNLESS the contrasts are non-orthogonal, which is often the case when more than two hypothesis tests. If the contrasts are not orthogonal, some type of adjustment (e.g. Bonferroni) is required, which will lower the power you would otherwise gain with a planned contrast. Casey - Casey terHorst Ecology & Evolution Program Department of Biological Science Florida State University 319 Stadium Drive King Life Science Building Tallahassee, FL 32306-4295 terho...@bio.fsu.edu Quoting "Asaf Sadeh" : I am planning a 2x2 factorial experiment whe Dear list members, I am planning a 2x2 factorial experiment where I record several response variables to test several hypotheses. Some of these hypotheses can be tested using the usual 2-way ANOVA. That is, the significance or non significance of the two main effects and their interaction is expected to provide sufficient information to draw conclusions regarding these hypotheses. However, another hypothesis focuses on one of the four treatment combinations, and would be best approached by comparing this focal treatment with the other three. However, if I use the 2-way ANOVA, some possible results may be inconclusive, and require further "post hoc" analyses with a reduced threshold for significance. Since my a-priori hypothesis calls for 3 specific contrasts, it makes statistical sense to me that I can skip the 2-way ANOVA and only perform these 3 contrasts without reducing the significance threshold. The logic behind this is that these 3 planned contrasts replace the 3 component tests of the 2-way ANOVA procedure (2 for the main effects and one for their interaction) that are each always done without any change to the significance threshold. Though I have found support for this approach on online statistics lectures notes, I have never seen it taken in any published study, and I wonder if it is indeed kosher (and if it can be expected to pass reviewers). I would highly appreciate input on this, and especially references to back this approach in case it is valid. Thank you very much, Asaf
