Thanks for the reply Steve, yes, x is an attribute of orgs - for
instance - dummy of whether they are for profit or not.
So, tab forprofit wavenumber (pweight= number of clients)
my total sample for both waves is 1118 orgs
I basically want to run a chi-square or a t-test between an org
attribute and wavenumber but weight by number of clients.
I tried the svyset - (pweight=number of clients), and then use svy: tab
forprofit wavenumber - but I get an ackward result.
or the
*Normal Chi-square has a huge N*
. tab pfp wavenum, row col chi
+-------------------+
| Key |
|-------------------|
| frequency |
| row percentage |
| column percentage |
+-------------------+
| wavenum
pfp dummy | 4 6 | Total
-----------+----------------------+----------
0 | 527 430 | 957
| 55.07 44.93 | 100.00
| 86.11 77.48 | 82.01
-----------+----------------------+----------
1 | 85 125 | 210
| 40.48 59.52 | 100.00
| 13.89 22.52 | 17.99
-----------+----------------------+----------
Total | 612 555 | 1,167
| 52.44 47.56 | 100.00
| 100.00 100.00 | 100.00
Pearson chi2(1) = 14.7018 Pr = 0.000
. tab pfp wavenum [pweight= nuosatcl], row col chi
pweight not allowed
*Using survey option - reports low column percentages.
*
. svyset
pweight: nuosatcl
VCE: linearized
Single unit: missing
Strata 1: <one>
SU 1: <observations>
FPC 1: <zero>
. svy:tab pfp wavenum
(running tabulate on estimation sample)
Number of strata = 1 Number of obs
= 1121
Number of PSUs = 1121 Population size = 696235
Design
df = 1120
-------------------------------
| wavenum
pfp dummy | 4 6 Total
----------+--------------------
0 | .4576 .3995 .857
1 | .048 .095 .143
|
Total | .5056 .4944 1
-------------------------------
Key: cell proportions
Pearson:
Uncorrected chi2(1) = 21.5824
Design-based F(1, 1120) = 5.1446 P = 0.0235
*For MEANS*
. svy: mean latinclients, over(wavenum)
(running mean on estimation sample)
Survey: Mean estimation
Number of strata = 1 Number of obs = 1088
Number of PSUs = 1088 Population size = 673329
Design df
= 1087
4: wavenum = 4
6: wavenum = 6
--------------------------------------------------------------
| Linearized
Over | Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
latinclients |
4 | 11.36198 .9582807 9.481693 13.24227
6 | 17.05415 1.98646 13.15642 20.95188
--------------------------------------------------------------
. test [latinclients]4 - [ latinclients]6=0
Adjusted Wald test
( 1) [latinclients]4 - [latinclients]6 = 0
F( 1, 1087) = 6.66
Prob > F = 0.0100
.
.
. Erick
Steven Samuels wrote:
Martin's suggestions of -svy: tab- , with "organization' designated as
the psu, is probably the right one. However, I'm not sure. With your
specification "x" and "y" must be attributes of the organizations. One
must be "wave". What is the other? -pweight- will weight the
organizations by the number of clients. So, essentially you are
classifying clients by the attribute of their organization and
ignoring organization , except to compute standard errors. For
example, if you classify organizations as "big" and "small", -svy:
tab- would compare the proportions of clients who are in big
organizations in 1995 and 2005 Is this what you want?
Are the 618 organizations a sample of a population? If so, please
describe the design, for you need to take into account other aspects
of the design. Final question: what do you mean by "adjust for N"?
-Steve
On Nov 14, 2008, at 12:24 PM, Martin Weiss wrote:
Have you checked out -help svy: tabulate twoway-?
HTH
Martin
-------- Original-Nachricht --------
Datum: Fri, 14 Nov 2008 09:52:33 -0600
Von: Erick Guerrero <[email protected]>
An: [email protected]
Betreff: st: Comparing frequencies with pweight
Hi, I need code for Stata to do descriptives - chi-squares with
p-weights and adjust for N.
I am trying to compare percentages between two waves (1995 and 2005) on
618 organizations.
The tab x y, col row chi with pweight (number of clients in each
organization) does not work, and when I use fweight gives me an
inflated
N. What is the proper way to compare these frequencies in organizations
and weight by number of clients and adjust for N in stata?
Thanks,
Erick
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*
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*
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