SPSS F-test on change in R square between hierarchical models

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 at 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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