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st: What form of data needed for ipf function?


From   lcrawley@stanford.edu
To   statalist@hsphsun2.harvard.edu
Subject   st: What form of data needed for ipf function?
Date   Fri, 15 Aug 2008 10:05:23 -0700

I apparently don't have my data in a form that allows stata v 10.1 to run the ipf function.

I have a dataset of 262 observations coded by 6 variables, all categorical and all, hypothetically, independent.

varlist is
genre
race
type
condition
fda_cat
page_size


I ran a multiple correspondence analysis (using XLStat) to look at patterns with and without the binary variable (race). It was recommended that I should also run log-linear models on the data.

What form does the data need to be in for stata to perform the ipf command? I have tried several forms:
1. full spreadsheet data of 262 observations, each observation coded with string variables. Six variables of interest, range from dichotomous choices, three choices, or five choices. None are ordinal. All categorical.
describe

Contains data
obs: 262
vars: 6
size: 14,410 (99.9% of memory free)
---------------------------------------------------------------------------------
storage display value
variable name type format label variable label
---------------------------------------------------------------------------------
genre str3 %9s
race byte %8.0g
type str7 %9s
condition str28 %28s
fda_cat str4 %9s
page_size str4 %9s

2. multiway contingency (freq) table, where freq counts of 262 observations were combined into like combinations showing 63 similar observations (rows). The frequencies (cell counts) for each of the 63 rows ranged from 1 to 35.

Contains data from C:\Documents and Settings\LaVera Crawley\Desktop\transformed

 log linear data.dta
obs: 63
vars: 7 14 Aug 2008 20:52
size: 1,008 (99.9% of memory free)
-------------------------------------------------------------------------------
storage display value
variable name type format label variable label
-------------------------------------------------------------------------------
genre byte %8.0g
race byte %8.0g
type byte %8.0g
condition byte %8.0g
fda_cat byte %8.0g
page_size byte %8.0g
freq int %8.0g
------------------------------------------

Neither form of the data worked. I still get the error r(109) type mismatch message as below (despite what linear equation I use - with or without interaction terms):
For example:
. ipf [fw=freq], fit( race+ genre+ type+ condition+ fda_cat+ page_size)
Deleting all matrices......

Expansion of the various marginal models
----------------------------------------
marginal model 1 varlist : race
marginal model 2 varlist : genre
marginal model 3 varlist : type
marginal model 4 varlist : condition
marginal model 5 varlist : fda_cat
marginal model 6 varlist : page_size
unique varlist race genre type condition fda_cat page_size
invalid syntax
r(198);




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