6
Estimating Community Wide Effects of FC Adoption_supplementary materials
. psmatch2 fcinfn0 know sex age fcsee stinohepc hivseek fcblfrc mcsex30 fcmediaS hiv , outcome (fconeve) common logit ate
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Variable Sample | Treated Controls Difference S.E. T-stat
------+------
fconeve Unmatched | .391891892 .18 .211891892 .046920282 4.52
ATT | .37593985 .203007519 .172932331 .074264372 2.33
ATU | .214285714 .285714286 .071428571 . .
ATE | .11627907 . .
------+------
Note: S.E. does not take into account that the propensity score is estimated.
psmatch2: | psmatch2: Common
Treatment | support
assignment | Off suppo On suppor | Total
------+------+------
Untreated | 32 168 | 200
Treated | 15 133 | 148
------+------+------
Total | 47 301 | 348
repeat analysis without strong predictors, as suggested by reviewer:
w/o fcsee and fcmediaS
. psmatch2 fcinfn0 know sex age stinohepc hivseek fcblfrc mcsex30 hiv , outcome (fconeve) common
> logit ate
Logistic regression Number of obs = 348
LR chi2(8) = 45.46
Prob > chi2 = 0.0000
Log likelihood = -214.58581 Pseudo R2 = 0.0958
------
fcinfn0 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
------+------
know | -.2202235 .6493483 -0.34 0.735 -1.492923 1.052476
sex | .5037462 .2396115 2.10 0.036 .0341163 .9733762
age | -.0281476 .0109574 -2.57 0.010 -.0496237 -.0066715
stinohepc | .6094463 .2446059 2.49 0.013 .1300275 1.088865
hivseek | .8911438 .2455329 3.63 0.000 .409908 1.372379
fcblfrc | .5395844 .4034027 1.34 0.181 -.2510704 1.330239
mcsex30 | .3509394 .2363423 1.48 0.138 -.1122831 .8141619
hiv | .187482 .1420411 1.32 0.187 -.0909135 .4658774
_cons | -2.353749 1.256718 -1.87 0.061 -4.816871 .1093728
------
There are observations with identical propensity score values.
The sort order of the data could affect your results.
Make sure that the sort order is random before calling psmatch2.
------
Variable Sample | Treated Controls Difference S.E. T-stat
------+------
fconeve Unmatched | .391891892 .18 .211891892 .046920282 4.52
ATT | .391891892 .162162162 .22972973 .068224726 3.37
ATU | .178947368 .384210526 .205263158 . .
ATE | .215976331 . .
------+------
Note: S.E. does not take into account that the propensity score is estimated.
psmatch2: | psmatch2: Common
Treatment | support
assignment | Off suppo On suppor | Total
------+------+------
Untreated | 10 190 | 200
Treated | 0 148 | 148
------+------+------
Total | 10 338 | 348
repeat analysis without strong predictors, as suggested by reviewer:
w/o fcsee and fcmediaS and hivseek
. psmatch2 fcinfn0 know sex age stinohepc fcblfrc mcsex30 hiv , outcome (fconeve) common logit ate
Logistic regression Number of obs = 348
LR chi2(7) = 32.06
Prob > chi2 = 0.0000
Log likelihood = -221.28309 Pseudo R2 = 0.0676
------
fcinfn0 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
------+------
know | -.8272496 .6156692 -1.34 0.179 -2.033939 .3794398
sex | .5733057 .2344222 2.45 0.014 .1138466 1.032765
age | -.0294798 .0107454 -2.74 0.006 -.0505403 -.0084193
stinohepc | .5511488 .2386236 2.31 0.021 .083455 1.018843
fcblfrc | .5939295 .3964567 1.50 0.134 -.1831114 1.37097
mcsex30 | .390728 .2317195 1.69 0.092 -.0634338 .8448898
hiv | .2359905 .1377846 1.71 0.087 -.0340624 .5060435
_cons | -1.842781 1.219155 -1.51 0.131 -4.23228 .5467181
------
There are observations with identical propensity score values.
The sort order of the data could affect your results.
Make sure that the sort order is random before calling psmatch2.
------
Variable Sample | Treated Controls Difference S.E. T-stat
------+------
fconeve Unmatched | .391891892 .18 .211891892 .046920282 4.52
ATT | .394557823 .19047619 .204081633 .069676038 2.93
ATU | .180412371 .463917526 .283505155 . .
ATE | .249266862 . .
------+------
Note: S.E. does not take into account that the propensity score is estimated.
psmatch2: | psmatch2: Common
Treatment | support
assignment | Off suppo On suppor | Total
------+------+------
Untreated | 6 194 | 200
Treated | 1 147 | 148
------+------+------
Total | 7 341 | 348
. attnd fconeve fcinfn0 know sex age hivseek fcblfrc stinohepc mcsex30 fcsee fcmediaS hiv, comsup boot reps(100) dots logit detail
Estimation of the ATT with the nearest neighbor matching method
Random draw version
****************************************************************
Note: the common support option has been selected
The region of common support is [.11038721, .92812903]
The outcome is fconeve
Variable | Obs Mean Std. Dev. Min Max
------+------
fconeve | 321 .2959502 .4571814 0 1
The treatment is fcinfn0
fcinfn0 | Freq. Percent Cum.
------+------
no one spoke about FC | 168 53.16 53.16
someone spoke about FC positively or b | 148 46.84 100.00
------+------
Total | 316 100.00
The distribution of the pscore is
Pr(fcinfn0)
------
Percentiles Smallest
1% .1148199 .1103872
5% .1300056 .110692
10% .1603485 .111217 Obs 321
25% .3009036 .1148199 Sum of Wgt. 321
50% .4297598 Mean .4620596
Largest Std. Dev. .2242147
75% .619251 .9200741
90% .8168924 .9227483 Variance .0502722
95% .8728809 .9262863 Skewness .3600555
99% .9200741 .928129 Kurtosis 2.199449
The program is searching the nearest neighbor of each treated unit.
This operation may take a while.
****************************************************
Forward search
****************************************************
Backward search
****************************************************
Choice between backward or forward match
****************************************************
Display of final results
****************************************************
The number of treated is 148
The number of treated which have been matched is 148
Average absolute pscore difference between treated and controls
Variable | Obs Mean Std. Dev. Min Max
------+------
PSDIF | 148 .0063397 .0107588 4.65e-06 .0552482
Average outcome of the matched treated
Variable | Obs Mean Std. Dev. Min Max
------+------
fconeve | 148 .3918919 .4898304 0 1
Average outcome of the matched controls
Variable | Obs Weight Mean Std. Dev. Min Max
------+------
fconeve | 69 148 .1824324 .3890299 0 1
ATT estimation with Nearest Neighbor Matching method
(random draw version)
Analytical standard errors
------
n. treat. n. contr. ATT Std. Err. t
------
148 69 0.209 0.083 2.524
------
Note: the numbers of treated and controls refer to actual
nearest neighbour matches
Bootstrapping of standard errors
command: attnd fconeve fcinfn0 know sex age hivseek fcblfrc stinohepc mcsex30 fcsee fcmediaS hiv , pscore() logit comsup
statistic: attnd = r(attnd)
note: label truncated to 80 characters
Bootstrap statistics Number of obs = 398
Replications = 100
------
Variable | Reps Observed Bias Std. Err. [95% Conf. Interval]
------+------
attnd | 100 .2094595 -.0723294 .082463 .0458349 .373084 (N)
| -.0214286 .2875 (P)
| .1102941 .3178295 (BC)
------
Note: N = normal
P = percentile
BC = bias-corrected
ATT estimation with Nearest Neighbor Matching method
(random draw version)
Bootstrapped standard errors
------
n. treat. n. contr. ATT Std. Err. t
------
148 69 0.209 0.082 2.540
------
Note: the numbers of treated and controls refer to actual
nearest neighbour matches
repeat analysis without strong predictor, as suggested by reviewer:
w/o fcsee and fcmediaS
Analytical standard errors
------
n. treat. n. contr. ATT Std. Err. t
------
148 81 0.230 0.068 3.367
------
Note: the numbers of treated and controls refer to actual
nearest neighbour matches
Bootstrapped standard errors
------
n. treat. n. contr. ATT Std. Err. t
------
148 81 0.230 0.073 3.159
------
Note: the numbers of treated and controls refer to actual
repeat analysis without strong predictor, as suggested by reviewer:
w/o fcsee and fcmediaS and hivseek
Analytical standard errors
------
n. treat. n. contr. ATT Std. Err. t
------
148 83 0.203 0.069 2.933
------
Note: the numbers of treated and controls refer to actual
nearest neighbour matches
Bootstrapped standard errors
------
n. treat. n. contr. ATT Std. Err. t
------
148 83 0.203 0.074 2.740
------
sensatt fconeve fcinfn0 know sex age hivseek fcblfrc stinohepc mcsex30 fcsee fcmediaS hiv, p( unprsx) reps(100) comsup logit bootstrap
as suggested by reviewer: [2ND]
The probability of having U=1 if T=1 and Y=1 (p11) is equal to: 0.37
The probability of having U=1 if T=1 and Y=0 (p10) is equal to: 0.61
The probability of having U=1 if T=0 and Y=1 (p01) is equal to: 0.42
The probability of having U=1 if T=0 and Y=0 (p00) is equal to: 0.60
The probability of having U=1 if T=1 (p1.) is equal to: 0.51
The probability of having U=1 if T=0 (p0.) is equal to: 0.57
The program is iterating the ATT estimation with simulated confounder.
You have chosen to perform 100 iterations. This step may take a while.
ATT estimation with simulated confounder
General multiple-imputation standard errors
------
ATT Std. Err. Out. Eff. Sel. Eff.
------
0.141 0.100 0.537 0.922
------
Note: Both the outcome and the selection effect
are odds ratios from logit estimations.
So the unobserved confounder U accounts for (.209-.141 )/.209 = .32% of the baseline estimate, but the effect on both outcome and selection are negative, so we try another dummy.
sensatt fconeve fcinfn0 know sex age hivseek fcblfrc stinohepc mcsex30 fcsee fcmediaS hiv, p11(0.40) p10(0.40) p01(0.20) p00(0.20) reps(100) comsup logit
The probability of having U=1 if T=1 and Y=1 (p11) is equal to: 0.40
The probability of having U=1 if T=1 and Y=0 (p10) is equal to: 0.40
The probability of having U=1 if T=0 and Y=1 (p01) is equal to: 0.40
The probability of having U=1 if T=0 and Y=0 (p00) is equal to: 0.40
The probability of having U=1 if T=1 (p1.) is equal to: 0.40
The probability of having U=1 if T=0 (p0.) is equal to: 0.40
ATT estimation with simulated confounder
General multiple-imputation standard errors
------
ATT Std. Err. Out. Eff. Sel. Eff.
------
0.135 0.099 1.133 1.035
------
Note: Both the outcome and the selection effect
are odds ratios from logit estimations.
So the unobserved confounder U accounts for (.209-.135 )/.209 = .35% of the baseline estimate, which seems sizeable in fact.
pscore fcinfn0 know sex age hivseek fcblfrc stinohepc mcsex30 fcsee fcmediaS hiv, pscore( psb4c10) blockid( bl4cov10) comsup numblo(4) level(0.005) logit
*the solution with 5 blocks yielded a 5th group of 6 in non-exposed (30 in exposed), so tried 4 blocks;
The region of common support is [.11038721, .92812903]
Description of the estimated propensity score in region of common support
Estimated propensity score
------
Percentiles Smallest
1% .1148199 .1103872
5% .1300056 .110692
10% .1603485 .111217 Obs 321
25% .3009036 .1148199 Sum of Wgt. 321
50% .4297598 Mean .4620596
Largest Std. Dev. .2242147
75% .619251 .9200741
90% .8168924 .9227483 Variance .0502722
95% .8728809 .9262863 Skewness .3600555
99% .9200741 .928129 Kurtosis 2.199449
******************************************************
Step 1: Identification of the optimal number of blocks
Use option detail if you want more detailed output
******************************************************
The final number of blocks is 4
This number of blocks ensures that the mean propensity score
is not different for treated and controls in each blocks
**********************************************************
Step 2: Test of balancing property of the propensity score
Use option detail if you want more detailed output
**********************************************************
The balancing property is satisfied
This table shows the inferior bound, the number of treated and the number of controls for each block
Inferior |
of block | fcinfn0
of pscore | no one s someone | Total
------+------+------
.1103872 | 47 14 | 61
.25 | 86 50 | 136
.5 | 27 47 | 74
.75 | 8 37 | 45
------+------+------
Total | 168 148 | 316
Note: the common support option has been selected
. logit fcinfn0 know sex age hivseek fcblfrc stinohepc mcsex30 fcsee fcmediaS hiv, nolog
Logistic regression Number of obs = 348
LR chi2(10) = 89.75
Prob > chi2 = 0.0000
Log likelihood = -192.4429 Pseudo R2 = 0.1891
------
fcinfn0 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
------+------
know | .0723086 .6987278 0.10 0.918 -1.297173 1.44179
sex | .4650407 .255435 1.82 0.069 -.0356028 .9656842
age | -.0173805 .0119044 -1.46 0.144 -.0407126 .0059516
hivseek | .7305862 .2642011 2.77 0.006 .2127614 1.248411
fcblfrc | .4206706 .4329957 0.97 0.331 -.4279853 1.269326
stinohepc | .4436606 .2616602 1.70 0.090 -.069184 .9565053
mcsex30 | .2827335 .2529966 1.12 0.264 -.2131307 .7785976
fcsee | 1.506495 .332786 4.53 0.000 .8542462 2.158743
fcmediaS | 1.415616 .3826396 3.70 0.000 .6656558 2.165575
hiv | .1551879 .1512385 1.03 0.305 -.141234 .4516099
_cons | -3.767882 1.381353 -2.73 0.006 -6.475284 -1.06048
------
. linktest, nolog
Logistic regression Number of obs = 348
LR chi2(2) = 89.78
Prob > chi2 = 0.0000
Log likelihood = -192.42592 Pseudo R2 = 0.1892
------
fcinfn0 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
------+------
_hat | .9934277 .1310549 7.58 0.000 .7365647 1.250291
_hatsq | -.0158106 .0858107 -0.18 0.854 -.1839965 .1523752
_cons | .0144738 .1501139 0.10 0.923 -.2797439 .3086916
------