Hi Jeff,
Re: the first issue. There are guidelines regarding sample size requirements for multiple regression, but I couldn't find any guidelines regarding whether dichotomous predictors have to have a certain amount of cases per group. I know SPSS will run the analysis anyway, but I imagine results aren't reliable unless there are say more than 20 cases per group. As you say, "you may get an estimate for the regression coefficient, but the p value will be high".
I follow what you're saying in your example about interactions. I thought there would be a simple way to look at it :-)
Thank you for your help Jeff.
K S Scot
From: Jeff <[hidden email]>
Reply-To: Jeff <[hidden email]>
To: [hidden email]
Subject: Re: Multiple Regression & Interactions
Date: Mon, 7 Aug 2006 09:35:37 -0600
>At 06:01 AM 8/7/2006, you wrote:
>>Does anyone know whether there are sample size requirements for
>>dichotomous
>>predictors in multiple regression? That is, for the dichotomous
>>predictor,
>>what is the smallest number of cases per group that is allowed?
>>
>>Also, I have another query regarding interpreting interaction
>>effects in
>>SPSS's multiple regression. When a cross product term is created
>>by
>>multiplying together a predictor which is positively associated
>>with the DV
>>(e.g., happiness) and a predictor that is negatively associated
>>with the DV
>>(e.g., depression), would the resulting product term be expected to
>>show a
>>positive or negative beta coefficient? I'm sure there's a really
>>simple
>>answer to this.
>>
>>Thank you in advance.
>>K S Scot
>
>
>Regarding the first issue - I'm not sure I understand -
>mathematically, the
>number of cases doesn't matter as long as it isn't a constant -
>e.g., all
>cases are in the same group. Practically, if you have a small number
>of
>cases in one group, you won't be able to accurately examine the
>group
>differences - i.e., you may get an estimate for the regression
>coefficient,
>but the p value will be high.
>
>Regarding the second issue - the sign of the bivariate correlations
>doesn't
>really matter. What matters is whether there is an interaction
>between the
>effects (by definition). In other words, let's say Happy-days/month
>is
>positively related to amount of time spent outside of house/month,
>while
>depression/month is negatively related. A significant interaction,
>for
>example, might imply that if there are many depressed days/month,
>the
>desire to go outside during happy days is reduced.
>
>
>
>
>
>
>Jeff
| Free forum by Nabble | Edit this page |