homework06.Rmd

---
title: "Homework 06 - Logistic Regression"
---

## Homework 06 - Logistic Regression - due 12/05/2018

### HELP Dataset

For Homework 06, you will be using the HELP dataset, learn more at:

* [https://melindahiggins2000.github.io/N736Fall2017_HELPdataset/](https://melindahiggins2000.github.io/N736Fall2017_HELPdataset/) &
* [https://github.com/melindahiggins2000/N736Fall2017_HELPdataset](https://github.com/melindahiggins2000/N736Fall2017_HELPdataset)

### Previous Exercises to Refer to

Refer to the logistic regression analysis example and codes we ran during lesson 18 and 19 - see [https://github.com/melindahiggins2000/N736Fall2017_lesson1819](https://github.com/melindahiggins2000/N736Fall2017_lesson1819)

### Variables to Consider in HELP Dataset

For the HELP dataset:

* OUTCOME VARIABLE: 
    - consider the variable `e2b` "Number of times in past 6 months entered a detox program - Baseline" 
    - recode this into a new variable `nodetox` for those who did NOT say they had entered a detox program 6mo prior to baseline and those who did 1 or more times (i.e. code the `e2b` missing as 1 and non-missing as 0 - see codes below to help you get started)
* PREDICTOR VARIABLE: consider these variables as potential predictors for `nodetox`:
    - `age`, `female`, `pss_fr`, `pcs`, `mcs`, and `cesd`

### Code to help you get started

* SPSS Code [https://github.com/melindahiggins2000/N736/raw/master/homework6_SPSSSyntax1.sps](https://github.com/melindahiggins2000/N736/raw/master/homework6_SPSSSyntax1.sps)
* SAS Code [https://github.com/melindahiggins2000/N736/raw/master/homework6_SAScode.sas](https://github.com/melindahiggins2000/N736/raw/master/homework6_SAScode.sas)
* R Code [https://github.com/melindahiggins2000/N736/raw/master/homework06_Rcode.R](https://github.com/melindahiggins2000/N736/raw/master/homework06_Rcode.R)

### Assignment

Complete the following:

1. Consider the continuous variable `mcs` as a predictor for `nodetox`
    a. run a logistic regression of the probability of not being in a detox program prior to baseline (`nodetox`) given their mental health scores (`mcs`)
    b. make a plot of the the predicted probability of no detox (`nodetox`) by the mental health scores (`mcs`)
    c. what value of the `mcs` leads to a probability of not being in a detox program => 0.5? _(hint: use the plot you just made)_
    
2. Run a logistic regression model for the probability of not being in a detox program 6mo prior to baseline considering all of these possible predictor variables: `age`, `female`, `pss_fr`, `pcs`, `mcs`, and `cesd`:
    a. present the final model results (B, SE(of B), p-values, Odds Ratios, and 95% confidence intervals for the Odds Ratios)
    b. write a few sentences describing your results including:
        i. model fit _(report the Area Under the Curve (AUC) and include a ROC plot)_ - discuss if you think this is a good model or not for predicting not being in a detox program 6mo prior to baseline
        ii. model classification table results - remember to report the threshold used for the classification table - you can change it from 0.5 if you think a different threshold might work better
        iii. odds ratios for each significant predictor in the model _("...for every 1 unit change in the predictor the odds of not being in a detox program prior to baseline was x.xxx times higher/lower...")_

### Variables in HELP dataset to be used for Homework 06:

```{r, echo=FALSE, message=FALSE, warning=FALSE}
helpdata <- readRDS("helpmkh.rds")
library(tidyverse)
sub1 <- helpdata %>%
  select(e2b, age, female, pss_fr,
         pcs, mcs, cesd)

# create a function to get the label
# label output from the attributes() function
getlabel <- function(x) attributes(x)$label
# getlabel(sub1$age)

library(purrr)
ldf <- purrr::map_df(sub1, getlabel) # this is a 1x15 tibble data.frame
# t(ldf) # transpose for easier reading to a 15x1 single column list

# using knitr to get a table of these
# variable names for Rmarkdown
library(knitr)
knitr::kable(t(ldf),
             col.names = c("Variable Label"),
             caption="Use these variables from HELP dataset for Homework 06")

```

## ANSWER KEY Files and Output

* [R Code](https://github.com/melindahiggins2000/N736Fall2017_Homework6Key/raw/master/Homework6Key_Rcode_2018.R)
* [R Output - in HTML format from `rmarkdown`](https://melindahiggins2000.github.io/N736Fall2017_Homework6Key/Homework6Key_Rcode_2018.html)

* [SAS Code](https://github.com/melindahiggins2000/N736Fall2017_Homework6Key/raw/master/homework6_SAScode_Key2018.sas)
* [SAS Output in HTML format](https://melindahiggins2000.github.io/N736Fall2017_Homework6Key/SASOutput_Homework6Key_2018.htm)

* [SPSS Code](https://github.com/melindahiggins2000/N736Fall2017_Homework6Key/raw/master/homework6_SyntaxSPSS_Key2018.sps)
* [SPSS Output in HTML format](https://melindahiggins2000.github.io/N736Fall2017_Homework6Key/SPSSOutput_Homework6Key_2018.html)