If you have decided to use RStudio:

Model $1$

Run a logit model and use being a member of network and find out its impact on hospital ownership and hospital beds? $($Model $1)$

Model $2$

Now, include hospital income and report the Coeff.? $($Model $2)$

Model $3$

Now, include the ratio of ratio$-$Medicare$-$discharge and ratio$-$Medicaid$-$discharge in your model? And keep all variables you used for models $1,2$ & $3$ and discuss your findings? Do you recommend keeping membership for a hospital? Why or why not? $($Model $3)$

Based on your finding please recommend $3$ policies to improve hospital performance in FP$,$ NFP hospitals, please make sure to use the final model for your recommendation. # You can remove the # from the sink command to keep all log in txt$.$

# sink$("$C:$/$UMUC$/$week$5$exercise.txt$")$

# Step $1$: Install package dplyr & load it

# install.packages$(\text{'}$dplyr$\text{'})$

library$($dplyr$)$

# Step $2$: Read your data

# Pl change the location of file

hosp $<-$ read.csv$("$C:$/$UMUC$/$HMGT$400$HOSPITAL.csv$",$ header$=$T$,$ sep $=\text{'},\text{'})$

#Step $3$: See the variables' names

names $($hosp$)$

#step $4$ : generate benefit variable

hosp$benefit $<-($hosp$total$\_$hosp$\_$revenue$-$hosp$total$\_$hosp$\_$cost$)$

hosp$medicare$\_$discharge$\_$ratio $<-($hosp$total$\_$hospital$\_$medicare$\_$discharg$/$hosp$total$\_$hospital$\_$discharges$)*100$

hosp$medicaid$\_$discharge$\_$ratio $<-($hosp$total$\_$hospital$\_$medicaid$\_$discharg$/$hosp$total$\_$hospital$\_$discharges$)*100$

#step $5$ : generate own$1$ as a categorical variable

## Ownership

## $0)$ non$-$for$-$profit

## $1)$ for profit

## $2)$ Public

## $3)$ Other

own$1<-$ factor$($hosp$own, levels $=$ c$(0,1,2,3))$

#step $6$ : Run logit models

# Model $1$

model$1<-$ glm$($system$\_$member ~ own$1+$ hospital$\_$beds,family$=$binomial$($link$=$'logit'$),$data$=$hosp$)$

summary$($model$1)$

# Model $2$

model$2<-$ glm$($system$\_$member ~ own$1+$ hospital$\_$beds $+$ total$\_$hosp$\_$revenue,family$=$binomial$($link$=$'logit'$),$data$=$hosp$)$

summary$($model$2)$

# Model $3$

model$3<-$ glm$($system$\_$member ~ own$1+$ hospital$\_$beds $+$ total$\_$hosp$\_$revenue $+$ medicare$\_$discharge$\_$ratio $+$ medicaid$\_$discharge$\_$ratio,family$=$binomial$($link$=$'logit'$),$data$=$hosp$)$

summary$($model$3)$

# sink$()$

model$1<-$ glm$($system$\_$member ~ hospital$\_$beds,family$=$binomial$($link$=$'logit'$),$data$=$hosp$)$

summary$($model$1)$

model$2<-$ glm$($system$\_$member ~ hospital$\_$beds $+$ total$\_$hosp$\_$revenue,family$=$binomial$($link$=$'logit'$),$data$=$hosp$)$

summary$($model$2)$

model$3<-$ glm$($system$\_$member ~ hospital$\_$beds $+$ total$\_$hosp$\_$revenue $+$ medicare$\_$discharge$\_$ratio $+$ medicaid$\_$discharge$\_$ratio,family$=$binomial$($link$=$'logit'$),$data$=$hosp$)$

summary$($model$3)$