Dear all:
Anybody has any idea what can be done in the case below?
Thanking you,
Mihir
On Wed, Sep 30, 2009 at 1:29 AM, Mihir <[email protected]> wrote:
>
> Dear all:
>
> I am stuck with a problem in pearson chi-square test with survey
> command. I have setup survey setting for Nationwide Inpatient Survey
> (NIS) data. I used hospital id as sampling unit, discwt as sampling
> weight and stratum variable as strata as suggested on NIS website.
> When I am trying to run chi-square test for independence between age
> category and year of data collection from 1998 to 2007, it gives
> proper result, but when I run the same command by retaining only two
> years (1998 and 2007), it does not produce p-value. I don't understand
> why it is happening? Can anybody help me - what I should do? I am also
> getting similar results with other variables that same command works
> with more year but doesn't work with two years.
>
> I have pasted my output for your ready reference.
>
> Thanking you in advance,
> Mihir
>
> svyset hospid [pweight=discwt], strata(stratum) vce(linearized)
>
> pweight: discwt
> VCE: linearized
> Strata 1: stratum
> SU 1: hospid
> FPC 1: <zero>
>
> svy: tabulate year age2cat, count column row obs percent format(%10.0g) pearson
> (running tabulate on estimation sample)
>
> Number of strata = 60 Number of obs = 157222
> Number of PSUs = 3270 Population size = 759816.12
> Design df = 3210
>
> -------------------------------------------
> | age2cat
> YEAR | <65 year >=65 yea Total
> ----------+--------------------------------
> 1998 | 27548.394 10497.654 38046.048
> | 72.408029 27.591971 100
> | 4.9658285 5.1193873 5.0072705
> | 5452 2102 7554
> |
> 1999 | 25591.467 9586.1825 35177.649
> | 72.749224 27.250776 100
> | 4.613076 4.6748901 4.6297582
> | 5265 1991 7256
> |
> 2000 | 25067.72 9839.9109 34907.631
> | 71.811576 28.188424 100
> | 4.5186663 4.7986258 4.5942209
> | 5163 2032 7195
> |
> 2001 | 24673.646 9882.7968 34556.443
> | 71.401001 28.598999 100
> | 4.4476311 4.8195399 4.5480007
> | 4983 1976 6959
> |
> 2002 | 83751.067 30869.413 114620.48
> | 73.068152 26.931848 100
> | 15.096831 15.054075 15.085292
> | 17682 6513 24195
> |
> 2003 | 80686.437 27375.013 108061.45
> | 74.66718 25.33282 100
> | 14.544405 13.349963 14.222053
> | 17002 5737 22739
> |
> 2004 | 77406.999 26898.738 104305.74
> | 74.211641 25.788359 100
> | 13.953259 13.117698 13.72776
> | 16052 5540 21592
> |
> 2005 | 74552.231 27032.143 101584.37
> | 73.389467 26.610533 100
> | 13.438663 13.182755 13.3696
> | 15263 5507 20770
> |
> 2006 | 68720.522 26875.807 95596.329
> | 71.886152 28.113848 100
> | 12.387449 13.106515 12.581508
> | 14234 5538 19772
> |
> 2007 | 66760.785 26199.193 92959.979
> | 71.816696 28.183304 100
> | 12.03419 12.776551 12.234536
> | 13813 5377 19190
> |
> Total | 554759.27 205056.85 759816.12
> | 73.012306 26.987694 100
> | 100 100 100
> | 114909 42313 157222
> -------------------------------------------
> Key: weighted counts
> row percentages
> column percentages
> number of observations
>
> Pearson:
> Uncorrected chi2(9) = 91.4953
> Design-based F(7.98, 25611.84)= 3.0966 P = 0.0017
>
> keep if year==1998|year==2007
>
> svy: tabulate year age2cat, count column row obs percent format(%10.0g) pearson
> (running tabulate on estimation sample)
>
> Number of strata = 60 Number of obs = 26744
> Number of PSUs = 1205 Population size = 131006.03
> Design df = 1145
>
> -------------------------------------------
> | age2cat
> YEAR | <65 year >=65 yea Total
> ----------+--------------------------------
> 1998 | 27548.394 10497.654 38046.048
> | 72.408029 27.591971 100
> | 29.210724 28.60642 29.041449
> | 5452 2102 7554
> |
> 2007 | 66760.785 26199.193 92959.979
> | 71.816696 28.183304 100
> | 70.789276 71.39358 70.958551
> | 13813 5377 19190
> |
> Total | 94309.179 36696.848 131006.03
> | 71.988428 28.011572 100
> | 100 100 100
> | 19265 7479 26744
> -------------------------------------------
> Key: weighted counts
> row percentages
> column percentages
> number of observations
>
>
> Pearson:
> Uncorrected chi2(1) = 0.9557
> Design-based F(., .) = . P = .
>
> *
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*
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