# REPRODUCE INFERENTIAL TABLES (3-5) FROM PRIOR PAPER
rm(list=ls())
# Set working directory ---------------------------
setwd("/Volumes/caas/CADRE CLC Data Project5/Clean Data/AK-SU-NETWORKS-ROUT")
# Load libraries ---------------------------
library(haven)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
# Load data ---------------------------
load("eda.RData")
# TAB 3: GLM, outcome: substance use, COVs: CDC guideline adherence ---------------------------
tab3_covs <- cov_dt %>%
select(gender_3cat, ethnicity, essential_worker, income,
covid_test,
daily_drinking, daily_opioid
)
tab3_lm <- lm(data=tab3_covs, cdc_avg_out ~ .)
summary(tab3_lm)
##
## Call:
## lm(formula = cdc_avg_out ~ ., data = tab3_covs)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.13558 -0.38166 0.05942 0.45349 1.26761
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 2.16965 0.07911 27.424
## gender_3catcisgender_male -0.15434 0.03591 -4.297
## gender_3catnon-binary/other/prefer not to answer -0.28390 0.13721 -2.069
## ethnicityhispanic -0.04098 0.04337 -0.945
## essential_workeryes -0.05291 0.04094 -1.292
## income 0.02487 0.01048 2.373
## covid_testnegative 0.08902 0.04762 1.869
## covid_testpositive -0.07286 0.09629 -0.757
## daily_drinkingdaily -0.06784 0.06815 -0.995
## daily_drinking1-6 days 0.09358 0.03975 2.354
## daily_opioiddaily -0.55676 0.09756 -5.707
## daily_opioid1-6 days -0.32893 0.05299 -6.207
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## gender_3catcisgender_male 1.89e-05 ***
## gender_3catnon-binary/other/prefer not to answer 0.0388 *
## ethnicityhispanic 0.3449
## essential_workeryes 0.1965
## income 0.0178 *
## covid_testnegative 0.0618 .
## covid_testpositive 0.4494
## daily_drinkingdaily 0.3198
## daily_drinking1-6 days 0.0187 *
## daily_opioiddaily 1.49e-08 ***
## daily_opioid1-6 days 7.70e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5827 on 1073 degrees of freedom
## Multiple R-squared: 0.1206, Adjusted R-squared: 0.1116
## F-statistic: 13.38 on 11 and 1073 DF, p-value: < 2.2e-16
# TAB 4: Logistic regression of SU vs any COVID-19 testing ---------------------------
#
# tab4_covs <-cov_dt %>%
# select(age, educationation, ethnicity,
# # add race
# essential_worker,
# income,
# household_size,
# daily_opioid
# )
# dim(tab)
# tab4_lm <- lm(data=tab4_covs, cov_dt$covid_test ~ .)
# summary(tab4_lm)
# TAB 5: LR, outcome stimulant use w/ +COVID-19 test, ---------------------------
## accounting for covariates, in the subset of participants
## reporting a COVID-19 test (n=279).
tab5_covs <-cov_dt %>%
select(ethnicity,
# add household size
# dwelling ownership
essential_worker,
income,
#add household size
daily_opioid
)