Date: Mon, 21 Jan 2008 21:05:08 0500
ReplyTo: Richard Ristow <wrristow@mindspring.com>
Sender: "SPSSX(r) Discussion" <SPSSXL@LISTSERV.UGA.EDU>
From: Richard Ristow <wrristow@mindspring.com>
Subject: Re: Dummy Coding and Interpreting Regression Analysis
InReplyTo: <2BDDE596EB04B6459ADDF6592D8AE3105CC91E@rowlandsrvr.Rowland
Reading.local>
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At 03:36 PM 1/18/2008, Justin Meyer wrote:
>I am working to determine if a subjective rating of schools'
>implementation is a predictor of posttest score for students in
>those schools. For the subjective rating of schools' implementation,
>schools are rated as tier 1, 2, or 3, with 1 being the best
>implementation and 3 being the worst. I am using a regression
>analysis, entering all of the variables at the same time. Because
>the tier status consists of three possible responses, I dummy coded
>it into two variables. The first variable is 1 for "Tier 2", 0 for
>"not Tier 2". The second variable is 1 for "Tier 3", and 0 for "not
>Tier 3". Is this the correct way to code this variable for a
>regression analysis?
It is certainly correct; there are some variations, that are also correct.
>I found a b (unstandardized coefficient) of 10.269 for Tier 2 and
>21.171 for Tier 3. Does this mean that, when all other variables are
>equal, students in Tier 2 score an average of 10 points less on the
>posttest and students in Tier 3 score an average of 21 points more
>on the posttest when compared to Tier 1?
It means exactly that. However, don't forget that these estimates
should be expressed as confidence intervals: "95% confidence interval
is...", and give the range. The 95% confidence interval is the
estimated value, +/ twice the standard error of estimate.
>The output from the regression, except for charts, is pasted below:
Thank you for that. However, you may see that it came through with so
many linebreaks added, that one can't do much with it.
So, does this get you farther?
Best of luck,
Richard Ristow
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