# Re: st: Anova

 From David Airey To "statalist@hsphsun2.harvard.edu" Subject Re: st: Anova Date Fri, 28 Nov 2008 09:04:28 -0600

No, I meant the difference in R-squared between the model with all variables vs the one with those of interest removed. But are you really interested in percent variation explained or a measure of effect size? It might also be worth interpreting the coefficients in terms of change in Y with a standardized change in X.
```
Sent from my iPhone

On Nov 28, 2008, at 8:35 AM, aapdm <aapdm_999@yahoo.co.uk> wrote:

```
```Dear David,

```
Thanks - so are you suggesting that I should regress Y on each of the explanatory variables separately and look at the R2 in each case?
```
Thanks, Alice.

--- On Fri, 28/11/08, David Airey <david.airey@vanderbilt.edu> wrote:

```
```From: David Airey <david.airey@vanderbilt.edu>
Subject: Re: st: Anova
To: statalist@hsphsun2.harvard.edu
Date: Friday, 28 November, 2008, 2:22 PM
This is true for balanced factorial ANOVA, but probably not

For a given variable, why not look at adjusted R^2 with
that variable (or group of dummies if categorical) in an out
of a regression model?

-Dave

On Nov 28, 2008, at 7:08 AM, aapdm wrote:

```
```Hi,

I am trying to use the anova command but I am not sure
```
```I am doing the right thing.
```
```
I have a dependent variable Y which I explain by 10
```
```explanatory variables, half of which are categorical while
the others are continuous.
```
```
When I use the anova command and specify which
```
```variables are continuous, then I get a table with the
Partial SS for each of the explanatory variables.
```
```
If I sum the Partial SS for all variables then this is
```
```much smaller than the value reported for the Model SS. How
is that the case? What am I missing here?
```
```
What I want to is to find to what extent each of the
```
```different explanatory variables explains the variance of the
dependent variable, which should be given by the ratio
between the Partial SS of each variable and the total SS. Am
I right?
```
```
Many thanks!

Alice.

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