Hi,

I am wondering if anyone knows how to perform an F-test on the change in R
square between hierarchical models in R? SPSS provides this information and
a researcher that I am working with is interested in getting this
information. Alternatively, if someone knows how I can calculate the test
statistic (SPSS calls it F-change?) and dfs that would be helpful as well.

The output and the test I am looking for is available here ->
http://dl.dropbox.com/u/1501309/spss_rsquared.pdf

Chris

On Wed, Nov 23, 2011 at 6:20 AM, Smart Guy <smartguy3k@gmail.com> wrote:

> Hi All,
>           I was adding a new row of data to my data frame using rbind(). I
> was surprised to see that after adding new row, I lost my data frame level
> attibute as well as  col level attribute. Please help me to insert a new
> row at frist or middle position so that my custom attribute is not lost.
>
>  Here is what I did.
>
> age<-c(15,20,18)
> weight<-c(40,42,30)
>
> ### creating my data frame ####
> mydata <- data.frame(age,weight)
>
> ### creating data frame level attribute ####
> attr(mydata,"myattr")<-c("myinfo")
>
> ### creating col level attribute for 'age' column  ###
> attr(mydata$age,"mycolattr")<-c("mycolinfo")
>
> #### Checking attributes  ###
> attributes(mydata)
> attributes(mydata$age)
>
> ### creating new row  #####
> newrow <- data.frame(age=16, weight= 42)
>
> #### Inserting newrow as first row to my data frame ####
> mydata<- rbind(newrow, mydata)
>
> #### Checking attributes again ###  I lost my custom attributes
> attributes(mydata$age)
> attributes(mydata)
>
>
> Thanks in advance,
>
>
> --
> SG
>
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>
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>

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