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```
Linear regression (ordinary least squares) for systolic blood pressure,
using two predictor variables: gender (RIAGENDR) and age (RIDAGEYR).
Gender is treated as a quantitative variable and is coded as 1 for
males and 2 for females.
Generalized linear model analysis
=======================================================================
Family: Gaussian Link: Identity
Variance: Constant Num obs: 6756
Scale: 227.879549
-----------------------------------------------------------------------
Variable Parameter SE LCB UCB Z-score P-value
-----------------------------------------------------------------------
icept 105.6458 0.6595 104.3268 106.9649 160.1817 0.0000
RIAGENDR -3.8397 0.3674 -4.5744 -3.1049 -10.4521 0.0000
RIDAGEYR 0.4964 0.0083 0.4798 0.5131 59.7942 0.0000
-----------------------------------------------------------------------
Linear regression (ordinary least squares) for systolic blood pressure,
including ethnicity as a categorical covariate, using level 5 (other
race/multiracial) as the reference category.
Generalized linear model analysis
=======================================================================
Family: Gaussian Link: Identity
Variance: Constant Num obs: 6756
Scale: 223.349181
-----------------------------------------------------------------------
Variable Parameter SE LCB UCB Z-score P-value
-----------------------------------------------------------------------
icept 103.8917 0.7566 102.3785 105.4049 137.3131 0.0000
RIAGENDR -3.9057 0.3638 -4.6334 -3.1781 -10.7352 0.0000
RIDAGEYR 0.4984 0.0084 0.4817 0.5152 59.5646 0.0000
RIDRETH1[1] 0.9441 0.6846 -0.4252 2.3134 1.3790 0.1679
RIDRETH1[2] 0.6704 0.7138 -0.7572 2.0980 0.9392 0.3476
RIDRETH1[3] 0.4462 0.5463 -0.6464 1.5387 0.8167 0.4141
RIDRETH1[4] 5.2583 0.5605 4.1372 6.3793 9.3810 0.0000
-----------------------------------------------------------------------
Linear regression (ordinary least squares) for systolic blood pressure,
including gender, age, ethnicity, and the interaction between gender
and age as covariates. Ethnicity is a categorical covariate with level
5 (other race/multiracial) as the reference category.
Generalized linear model analysis
=============================================================================
Family: Gaussian Link: Identity
Variance: Constant Num obs: 6756
Scale: 221.549555
-----------------------------------------------------------------------------
Variable Parameter SE LCB UCB Z-score P-value
-----------------------------------------------------------------------------
icept 110.9802 1.2116 108.5570 113.4034 91.5979 0.0000
RIAGENDR -8.6536 0.7315 -10.1166 -7.1905 -11.8295 0.0000
RIDAGEYR 0.3153 0.0259 0.2635 0.3671 12.1788 0.0000
RIDRETH1[1] 0.9754 0.6819 -0.3884 2.3392 1.4305 0.1526
RIDRETH1[2] 0.6228 0.7109 -0.7991 2.0447 0.8760 0.3810
RIDRETH1[3] 0.4482 0.5441 -0.6399 1.5364 0.8238 0.4100
RIDRETH1[4] 5.2657 0.5583 4.1492 6.3823 9.4323 0.0000
RIAGENDR:RIDAGEYR 0.1223 0.0164 0.0896 0.1551 7.4714 0.0000
-----------------------------------------------------------------------------
Regularized least squares regression (Lasso regression) for systolic
blood pressure, using equal penalty weights for all covariates and
zero penalty for the intercept.
Generalized linear model analysis
==================================================
Family: Gaussian Link: Identity
Variance: Constant Num obs: 6756
Scale: 223.361216
--------------------------------------------------
Variable Parameter
--------------------------------------------------
icept 104.0534
RIAGENDR -3.8632
RIDAGEYR 0.4986
RIDRETH1[1] 0.6319
RIDRETH1[2] 0.3424
RIDRETH1[3] 0.1836
RIDRETH1[4] 4.9899
--------------------------------------------------
Linear regression with systolic blood pressure as the outcome,
using a square root transform in the formula.
Generalized linear model analysis
==========================================================================
Family: Gaussian Link: Identity
Variance: Constant Num obs: 6756
Scale: 228.468869
--------------------------------------------------------------------------
Variable Parameter SE LCB UCB Z-score P-value
--------------------------------------------------------------------------
icept 112.1279 0.7234 110.6811 113.5748 154.9979 0.0000
RIAGENDR -3.8932 0.3680 -4.6291 -3.1572 -10.5802 0.0000
sqrt(RIDAGEYR) 0.0057 0.0001 0.0055 0.0059 57.5952 0.0000
RIDRETH1[1] 0.4459 0.6920 -0.9382 1.8299 0.6443 0.5194
RIDRETH1[2] 0.3749 0.7221 -1.0693 1.8191 0.5192 0.6037
RIDRETH1[3] 0.1662 0.5533 -0.9404 1.2729 0.3004 0.7639
RIDRETH1[4] 5.0373 0.5671 3.9031 6.1715 8.8828 0.0000
--------------------------------------------------------------------------
Logistic regression using high blood pressure status (binary) as
the dependent variable, and gender and age as predictors.
Generalized linear model analysis
=======================================================================
Family: Binomial Link: Logit
Variance: Binomial Num obs: 9338
Scale: 1.000000
-----------------------------------------------------------------------
Variable Parameter SE LCB UCB Z-score P-value
-----------------------------------------------------------------------
icept -3.8132 0.1267 -4.0665 -3.5598 -30.0968 0.0000
RIAGENDR -0.3762 0.0652 -0.5065 -0.2458 -5.7711 0.0000
RIDAGEYR 0.0663 0.0016 0.0631 0.0696 40.6338 0.0000
-----------------------------------------------------------------------
Generalized linear model analysis
===================================================
Family: Binomial Link: Logit
Variance: Binomial Num obs: 9338
Scale: 1.000000
---------------------------------------------------
Variable Parameter LCB UCB P-value
---------------------------------------------------
icept 0.0221 0.0171 0.0284 0.0000
RIAGENDR 0.6865 0.6026 0.7821 0.0000
RIDAGEYR 1.0686 1.0651 1.0721 0.0000
---------------------------------------------------
Parameters are shown as odds ratios
Elastic net penalized logistic regression for high blood pressure
status, with L1 and L2 penalties. Age and gender are the predictor
variables.
Generalized linear model analysis
==============================================
Family: Binomial Link: Logit
Variance: Binomial Num obs: 9338
Scale: 1.000000
----------------------------------------------
Variable Parameter
----------------------------------------------
icept -4.3464
RIAGENDR 0.0000
RIDAGEYR 0.0658
----------------------------------------------
```
|
