use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==0 & (BP_cat==0 | BP_cat==1)): logit BP_cat i.MJ, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 7,946
Subpop. size = 52,738,457.5
Design df = 109
F( 4, 106) = 1.91
Prob > F = 0.1145
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8973761 .0661503 -1.47 0.145 .7753959 1.038545
_IMJ_2 | .6995585 .1080518 -2.31 0.023 .515079 .9501107
_IMJ_3 | 1.155806 .3437167 0.49 0.627 .6410777 2.083816
_IMJ_4 | .904521 .2284574 -0.40 0.692 .5482956 1.492185
_cons | .2280199 .0109087 -30.90 0.000 .2073927 .2506987
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==0 & (BP_cat==0 | BP_cat==2)): logit BP_cat i.MJ, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 8,300
Subpop. size = 55,212,437.8
Design df = 109
F( 4, 106) = 1.89
Prob > F = 0.1180
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8525828 .0682291 -1.99 0.049 .727534 .999125
_IMJ_2 | .7739365 .1111255 -1.78 0.077 .5822556 1.02872
_IMJ_3 | .6433332 .2198738 -1.29 0.200 .3267777 1.266542
_IMJ_4 | .7788413 .169243 -1.15 0.253 .5062971 1.198098
_cons | .2971067 .0156086 -23.10 0.000 .267727 .3297104
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==0 & (BP_cat==0 | BP_cat==3)): logit BP_cat i.MJ, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 7,581
Subpop. size = 49,380,973.2
Design df = 109
F( 4, 106) = 1.57
Prob > F = 0.1880
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9273116 .0817424 -0.86 0.394 .7786639 1.104336
_IMJ_2 | .6920029 .1041564 -2.45 0.016 .5135131 .9325333
_IMJ_3 | .7410859 .2980164 -0.75 0.458 .3339858 1.644406
_IMJ_4 | .7979358 .2167948 -0.83 0.408 .4656985 1.367197
_cons | .1444932 .0100806 -27.73 0.000 .1258334 .1659199
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==1 & (BP_cat==0 | BP_cat==1)): logit BP_cat i.MJ, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 6,279
Subpop. size = 43,799,677
Design df = 109
F( 4, 106) = 1.66
Prob > F = 0.1652
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | 1.109859 .089886 1.29 0.201 .9452706 1.303105
_IMJ_2 | 1.182803 .1327996 1.50 0.138 .9468269 1.477591
_IMJ_3 | 1.457371 .3093195 1.77 0.079 .9569272 2.219533
_IMJ_4 | 1.383918 .2196616 2.05 0.043 1.010386 1.895543
_cons | .4168928 .0228766 -15.94 0.000 .3739307 .4647909
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==1 & (BP_cat==0 | BP_cat==2)): logit BP_cat i.MJ, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 6,856
Subpop. size = 47,763,794.7
Design df = 109
F( 4, 106) = 1.28
Prob > F = 0.2838
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | 1.116623 .0899385 1.37 0.174 .9518685 1.309895
_IMJ_2 | 1.016525 .1244252 0.13 0.894 .7975525 1.295618
_IMJ_3 | .8393784 .1818391 -0.81 0.421 .5463704 1.289521
_IMJ_4 | .8436662 .1414778 -1.01 0.313 .6050993 1.176291
_cons | .5680377 .0380708 -8.44 0.000 .4973795 .6487338
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==1 & (BP_cat==0 | BP_cat==3)): logit BP_cat i.MJ, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 5,820
Subpop. size = 39,649,749.3
Design df = 109
F( 4, 106) = 0.70
Prob > F = 0.5917
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | 1.084126 .0962073 0.91 0.365 .9092737 1.292602
_IMJ_2 | .9773222 .1430684 -0.16 0.876 .7311947 1.306299
_IMJ_3 | .8386504 .2162303 -0.68 0.496 .5030959 1.398013
_IMJ_4 | .8203393 .1609687 -1.01 0.315 .5560244 1.2103
_cons | .3144748 .0228819 -15.90 0.000 .2722419 .3632592
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 21,020
Subpop. size = 141,524,461
Design df = 109
F( 6, 104) = 210.20
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9599054 .0403027 -0.97 0.332 .8832601 1.043202
_IMJ_2 | 1.111107 .0745439 1.57 0.119 .9727652 1.269124
_IMJ_3 | 1.213377 .1784316 1.32 0.191 .9066055 1.623953
_IMJ_4 | 1.1299 .1107676 1.25 0.216 .930373 1.372216
gndr | 2.374512 .088687 23.15 0.000 2.205085 2.556956
ridageyr | 1.047735 .0020607 23.71 0.000 1.043659 1.051827
_cons | .0939611 .0077396 -28.71 0.000 .0798082 .1106239
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==0 & (BP_cat==0 | BP_cat==1)): logit BP_cat i.MJ gndr ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 7,946
Subpop. size = 52,738,457.5
Design df = 109
F( 5, 105) = 39.68
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8743377 .0663232 -1.77 0.079 .7522915 1.016184
_IMJ_2 | .94434 .1402459 -0.39 0.701 .7035507 1.267539
_IMJ_3 | 1.486765 .4645054 1.27 0.207 .8004207 2.761634
_IMJ_4 | 1.124858 .288705 0.46 0.648 .6763579 1.870764
gndr | 1 (omitted)
ridageyr | 1.052595 .0039248 13.75 0.000 1.044845 1.060402
_cons | .0291692 .0046804 -22.03 0.000 .0212232 .0400903
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==0 & (BP_cat==0 | BP_cat==2)): logit BP_cat i.MJ gndr ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 8,300
Subpop. size = 55,212,437.8
Design df = 109
F( 5, 105) = 58.63
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8474836 .069454 -2.02 0.046 .7204261 .9969495
_IMJ_2 | 1.090352 .1660338 0.57 0.571 .8062961 1.47448
_IMJ_3 | .7872003 .2569515 -0.73 0.465 .4122149 1.503304
_IMJ_4 | 1.031101 .2318588 0.14 0.892 .660308 1.61011
gndr | 1 (omitted)
ridageyr | 1.069099 .0043301 16.50 0.000 1.060551 1.077715
_cons | .019102 .0036778 -20.56 0.000 .0130422 .0279774
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==0 & (BP_cat==0 | BP_cat==3)): logit BP_cat i.MJ gndr ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 7,581
Subpop. size = 49,380,973.2
Design df = 109
F( 5, 105) = 157.39
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8915923 .087623 -1.17 0.246 .7337931 1.083325
_IMJ_2 | 1.247806 .2284854 1.21 0.229 .8680285 1.793743
_IMJ_3 | 1.142619 .5048698 0.30 0.763 .4759626 2.743025
_IMJ_4 | 1.164155 .3727837 0.47 0.636 .6171355 2.196044
gndr | 1 (omitted)
ridageyr | 1.115315 .0043666 27.88 0.000 1.106694 1.124004
_cons | .0012782 .0002562 -33.24 0.000 .0008592 .0019016
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==1 & (BP_cat==0 | BP_cat==1)): logit BP_cat i.MJ gndr ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 6,279
Subpop. size = 43,799,677
Design df = 109
F( 5, 105) = 1.44
Prob > F = 0.2161
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | 1.103874 .0904575 1.21 0.230 .9383921 1.298538
_IMJ_2 | 1.198661 .1346397 1.61 0.110 .9594264 1.497549
_IMJ_3 | 1.488963 .3217409 1.84 0.068 .9702595 2.284965
_IMJ_4 | 1.407392 .2278786 2.11 0.037 1.021045 1.939925
gndr | 1 (omitted)
ridageyr | 1.003871 .0032284 1.20 0.232 .9974929 1.01029
_cons | .3604478 .0480409 -7.66 0.000 .2767703 .4694239
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==1 & (BP_cat==0 | BP_cat==2)): logit BP_cat i.MJ gndr ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 6,856
Subpop. size = 47,763,794.7
Design df = 109
F( 5, 105) = 24.10
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | 1.083243 .0888474 0.97 0.332 .9207178 1.274456
_IMJ_2 | 1.157523 .1428256 1.19 0.238 .9064038 1.478215
_IMJ_3 | 1.013408 .2240619 0.06 0.952 .6538423 1.570708
_IMJ_4 | .9540503 .15945 -0.28 0.779 .6850358 1.328707
gndr | 1 (omitted)
ridageyr | 1.029965 .0029629 10.26 0.000 1.02411 1.035854
_cons | .1768818 .0223145 -13.73 0.000 .137751 .2271285
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==1 & (BP_cat==0 | BP_cat==3)): logit BP_cat i.MJ gndr ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 5,820
Subpop. size = 39,649,749.3
Design df = 109
F( 5, 105) = 62.50
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | 1.002395 .0954917 0.03 0.980 .8299272 1.210703
_IMJ_2 | 1.229048 .188078 1.35 0.181 .907506 1.664518
_IMJ_3 | 1.149222 .2961152 0.54 0.590 .6896303 1.915101
_IMJ_4 | 1.054878 .2298661 0.25 0.807 .6849143 1.62468
gndr | 1 (omitted)
ridageyr | 1.06245 .0038467 16.73 0.000 1.054854 1.070102
_cons | .0257684 .0044514 -21.18 0.000 .0182976 .0362895
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.AL_cat bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 67,991
Number of PSUs = 214 Population size = 292,944,878
Subpop. no. obs = 18,821
Subpop. size = 127,924,286
Design df = 109
F( 9, 101) = 171.42
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9195897 .0431616 -1.79 0.077 .8379031 1.00924
_IMJ_2 | 1.125541 .0807243 1.65 0.102 .9763994 1.297464
_IMJ_3 | 1.256641 .187487 1.53 0.129 .9349512 1.689016
_IMJ_4 | 1.136796 .1206675 1.21 0.230 .9211185 1.402973
gndr | 2.678669 .1097468 24.05 0.000 2.469751 2.905259
_IAL_cat_1 | 1.178936 .0645598 3.01 0.003 1.057679 1.314093
_IAL_cat_2 | 1.404028 .0972246 4.90 0.000 1.22397 1.610573
bmxbmi | 1.076922 .0039402 20.25 0.000 1.069141 1.08476
ridageyr | 1.048122 .0022665 21.73 0.000 1.043639 1.052623
_cons | .0092223 .0013177 -32.80 0.000 .0069479 .0122412
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==0 & (BP_cat==0 | BP_cat==1)): logit BP_cat i.MJ gndr ridageyr i.AL_cat bmxbmi, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 69,509
Number of PSUs = 214 Population size = 302,461,376
Subpop. no. obs = 7,265
Subpop. size = 48,654,780.3
Design df = 109
F( 8, 102) = 37.53
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8379907 .0699522 -2.12 0.037 .7102095 .9887623
_IMJ_2 | .8466709 .1391628 -1.01 0.313 .6112749 1.172716
_IMJ_3 | 1.21467 .400834 0.59 0.557 .6315586 2.336164
_IMJ_4 | .8496663 .2185 -0.63 0.528 .5103829 1.414492
gndr | 1 (omitted)
ridageyr | 1.051077 .0044012 11.90 0.000 1.04239 1.059836
_IAL_cat_1 | 1.08584 .110119 0.81 0.419 .8881237 1.327573
_IAL_cat_2 | 1.378243 .1980177 2.23 0.028 1.03671 1.83229
bmxbmi | 1.066562 .0060258 11.41 0.000 1.054686 1.078572
_cons | .004449 .0011393 -21.15 0.000 .0026783 .0073906
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==0 & (BP_cat==0 | BP_cat==2)): logit BP_cat i.MJ gndr ridageyr i.AL_cat bmxbmi, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 69,454
Number of PSUs = 214 Population size = 302,033,969
Subpop. no. obs = 7,564
Subpop. size = 50,701,354
Design df = 109
F( 8, 102) = 45.79
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .7954617 .0760442 -2.39 0.018 .6581622 .9614032
_IMJ_2 | 1.044568 .1689596 0.27 0.788 .7580691 1.439345
_IMJ_3 | .633661 .2296988 -1.26 0.211 .3089135 1.299802
_IMJ_4 | .9306533 .2315359 -0.29 0.773 .5683833 1.523823
gndr | 1 (omitted)
ridageyr | 1.070362 .0052019 13.99 0.000 1.060102 1.080722
_IAL_cat_1 | 1.207698 .122802 1.86 0.066 .9872662 1.477347
_IAL_cat_2 | 1.315207 .2103892 1.71 0.090 .9578595 1.805871
bmxbmi | 1.072536 .0055702 13.48 0.000 1.061552 1.083633
_cons | .0020805 .0006254 -20.54 0.000 .0011467 .0037748
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==0 & (BP_cat==0 | BP_cat==3)): logit BP_cat i.MJ gndr ridageyr i.AL_cat bmxbmi, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 69,512
Number of PSUs = 214 Population size = 302,597,226
Subpop. no. obs = 6,903
Subpop. size = 45,433,146.3
Design df = 109
F( 8, 102) = 77.84
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8962032 .1075588 -0.91 0.363 .706483 1.136871
_IMJ_2 | 1.172042 .2416903 0.77 0.443 .7788319 1.763773
_IMJ_3 | .4777004 .1865253 -1.89 0.061 .220323 1.035741
_IMJ_4 | 1.061533 .3605433 0.18 0.861 .5414798 2.08106
gndr | 1 (omitted)
ridageyr | 1.116414 .0051432 23.90 0.000 1.106267 1.126654
_IAL_cat_1 | 1.294265 .1641303 2.03 0.044 1.006625 1.664098
_IAL_cat_2 | 1.978136 .3570527 3.78 0.000 1.383215 2.828932
bmxbmi | 1.081111 .0077518 10.88 0.000 1.065856 1.096584
_cons | .000097 .0000333 -26.89 0.000 .0000491 .0001918
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==1 & (BP_cat==0 | BP_cat==1)): logit BP_cat i.MJ gndr ridageyr i.AL_cat bmxbmi, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 69,520
Number of PSUs = 214 Population size = 302,206,158
Subpop. no. obs = 5,609
Subpop. size = 39,460,782.4
Design df = 109
F( 8, 102) = 7.67
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | 1.014513 .0894296 0.16 0.870 .8518863 1.208186
_IMJ_2 | 1.193133 .1343428 1.57 0.120 .954488 1.491445
_IMJ_3 | 1.589181 .3661254 2.01 0.047 1.006622 2.508881
_IMJ_4 | 1.368357 .2468906 1.74 0.085 .956961 1.956611
gndr | 1 (omitted)
ridageyr | 1.004586 .0035906 1.28 0.203 .9974946 1.011728
_IAL_cat_1 | 1.16184 .113989 1.53 0.129 .9565255 1.411223
_IAL_cat_2 | 1.338886 .1380828 2.83 0.006 1.091368 1.642539
bmxbmi | 1.062421 .008483 7.58 0.000 1.04574 1.079368
_cons | .0617399 .0164256 -10.47 0.000 .0364389 .1046084
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==1 & (BP_cat==0 | BP_cat==2)): logit BP_cat i.MJ gndr ridageyr i.AL_cat bmxbmi, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 69,421
Number of PSUs = 214 Population size = 301,617,686
Subpop. no. obs = 6,087
Subpop. size = 42,836,427.5
Design df = 109
F( 8, 102) = 34.33
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | 1.062718 .0950656 0.68 0.498 .8900587 1.26887
_IMJ_2 | 1.309347 .1665492 2.12 0.036 1.017575 1.684781
_IMJ_3 | 1.306841 .2760889 1.27 0.208 .8597559 1.986415
_IMJ_4 | 1.139061 .2227807 0.67 0.507 .773032 1.678403
gndr | 1 (omitted)
ridageyr | 1.030069 .0031477 9.69 0.000 1.023849 1.036327
_IAL_cat_1 | 1.135591 .0971626 1.49 0.140 .9584612 1.345456
_IAL_cat_2 | 1.33981 .1308263 3.00 0.003 1.104064 1.625894
bmxbmi | 1.088814 .0070092 13.22 0.000 1.07501 1.102795
_cons | .014221 .0033136 -18.25 0.000 .0089611 .0225681
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1 & gndr==1 & (BP_cat==0 | BP_cat==3)): logit BP_cat i.MJ gndr ridageyr i.AL_cat bmxbmi, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
note: gndr omitted because of collinearity
Survey: Logistic regression
Number of strata = 105 Number of obs = 69,507
Number of PSUs = 214 Population size = 302,218,977
Subpop. no. obs = 5,137
Subpop. size = 35,323,673.6
Design df = 109
F( 8, 102) = 59.37
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9414976 .1028661 -0.55 0.582 .758184 1.169133
_IMJ_2 | 1.41268 .2440491 2.00 0.048 1.003097 1.989505
_IMJ_3 | 1.515046 .4069422 1.55 0.125 .8896639 2.580036
_IMJ_4 | 1.044303 .2549651 0.18 0.859 .6436855 1.694257
gndr | 1 (omitted)
ridageyr | 1.066267 .0047147 14.51 0.000 1.056964 1.075652
_IAL_cat_1 | 1.472201 .1750694 3.25 0.002 1.163077 1.863484
_IAL_cat_2 | 1.710912 .2258811 4.07 0.000 1.317004 2.222635
bmxbmi | 1.119031 .009425 13.35 0.000 1.100506 1.137868
_cons | .000685 .0002292 -21.77 0.000 .0003529 .0013297
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.For Table 3
use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
ta gndr MJ if include==1 pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
| Cannabis Use
Gender | Never Use Past Use 1-10 time 11-20 tim 21-30 tim | Total
-----------+-------------------------------------------------------+----------
Female | 5,572 3,960 698 128 321 | 10,679
Male | 4,131 4,344 993 278 595 | 10,341
-----------+-------------------------------------------------------+----------
Total | 9,703 8,304 1,691 406 916 | 21,020 use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
ta BP_cat MJ_cat if include==1,col
svy, subpop(if include==1): ta BP_cat MJ_cat,col percent pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
+-------------------+
| Key |
|-------------------|
| frequency |
| column percentage |
+-------------------+
| Cannabis Use Category
BP Category | Never Use Past Use Current U | Total
------------+---------------------------------+----------
Normal | 5,149 4,193 1,539 | 10,881
| 53.07 50.49 51.08 | 51.76
------------+---------------------------------+----------
Elevated | 1,478 1,311 555 | 3,344
| 15.23 15.79 18.42 | 15.91
------------+---------------------------------+----------
Stage 1 HTN | 1,938 1,760 577 | 4,275
| 19.97 21.19 19.15 | 20.34
------------+---------------------------------+----------
Stage 2 HTN | 1,138 1,040 342 | 2,520
| 11.73 12.52 11.35 | 11.99
------------+---------------------------------+----------
Total | 9,703 8,304 3,013 | 21,020
| 100.00 100.00 100.00 | 100.00
(running tabulate on estimation sample)
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 21,020
Subpop. size = 141,524,461
Design df = 109
--------------------------------------------------
BP | Cannabis Use Category
Category | Never Us Past Use Current Total
----------+---------------------------------------
Normal | 52.66 51.49 51.37 51.94
Elevated | 15.63 16.04 18.8 16.27
Stage 1 | 20.84 21.16 19.68 20.82
Stage 2 | 10.87 11.31 10.15 10.97
|
Total | 100 100 100 100
--------------------------------------------------
Key: column percentage
Pearson:
Uncorrected chi2(6) = 70.3954
Design-based F(5.56, 605.89) = 1.9542 P = 0.0758use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
ta BP_cat MJ_cat if include==1 & gndr==1,col
svy, subpop(if include==1 & gndr==1): ta BP_cat MJ_cat,col percent pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
+-------------------+
| Key |
|-------------------|
| frequency |
| column percentage |
+-------------------+
| Cannabis Use Category
BP Category | Never Use Past Use Current U | Total
------------+---------------------------------+----------
Normal | 1,770 1,739 798 | 4,307
| 42.85 40.03 42.77 | 41.65
------------+---------------------------------+----------
Elevated | 753 809 410 | 1,972
| 18.23 18.62 21.97 | 19.07
------------+---------------------------------+----------
Stage 1 HTN | 1,009 1,128 412 | 2,549
| 24.43 25.97 22.08 | 24.65
------------+---------------------------------+----------
Stage 2 HTN | 599 668 246 | 1,513
| 14.50 15.38 13.18 | 14.63
------------+---------------------------------+----------
Total | 4,131 4,344 1,866 | 10,341
| 100.00 100.00 100.00 | 100.00
(running tabulate on estimation sample)
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 10,341
Subpop. size = 71,193,951.1
Design df = 109
--------------------------------------------------
BP | Cannabis Use Category
Category | Never Us Past Use Current Total
----------+---------------------------------------
Normal | 43.49 41.02 42.51 42.15
Elevated | 18.13 18.98 22.83 19.37
Stage 1 | 24.7 26.02 22.55 24.94
Stage 2 | 13.68 13.98 12.1 13.54
|
Total | 100 100 100 100
--------------------------------------------------
Key: column percentage
Pearson:
Uncorrected chi2(6) = 189.5565
Design-based F(5.54, 604.35) = 2.4934 P = 0.0251use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
ta BP_cat MJ_cat if include==1 & gndr==0,col
svy, subpop(if include==1 & gndr==0): ta BP_cat MJ_cat,col percent pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
+-------------------+
| Key |
|-------------------|
| frequency |
| column percentage |
+-------------------+
| Cannabis Use Category
BP Category | Never Use Past Use Current U | Total
------------+---------------------------------+----------
Normal | 3,379 2,454 741 | 6,574
| 60.64 61.97 64.60 | 61.56
------------+---------------------------------+----------
Elevated | 725 502 145 | 1,372
| 13.01 12.68 12.64 | 12.85
------------+---------------------------------+----------
Stage 1 HTN | 929 632 165 | 1,726
| 16.67 15.96 14.39 | 16.16
------------+---------------------------------+----------
Stage 2 HTN | 539 372 96 | 1,007
| 9.67 9.39 8.37 | 9.43
------------+---------------------------------+----------
Total | 5,572 3,960 1,147 | 10,679
| 100.00 100.00 100.00 | 100.00
(running tabulate on estimation sample)
Number of strata = 105 Number of obs = 70,190
Number of PSUs = 214 Population size = 306,545,053
Subpop. no. obs = 10,679
Subpop. size = 70,330,509.5
Design df = 109
--------------------------------------------------
BP | Cannabis Use Category
Category | Never Us Past Use Current Total
----------+---------------------------------------
Normal | 59.89 62.82 66.03 61.85
Elevated | 13.66 12.85 12.12 13.13
Stage 1 | 17.79 15.91 14.93 16.65
Stage 2 | 8.654 8.417 6.927 8.361
|
Total | 100 100 100 100
--------------------------------------------------
Key: column percentage
Pearson:
Uncorrected chi2(6) = 131.1846
Design-based F(5.63, 613.53) = 2.1713 P = 0.0481