RR: Average risk ratio of a binary or continuous endogenous variable

Description

RR can be used to calculate the sample average risk ratio of a binary or continuous endogenous predictor/treatment, with corresponding interval obtained using posterior simulation.

Usage

RR(x, nm.end, E = TRUE, treat = TRUE, type = "bivariate", ind = NULL, 
   delta = FALSE, n.sim = 100, prob.lev = 0.05, hd.plot = FALSE,
   prob.plot = FALSE, main = "Histogram and Kernel Density of Simulated Risk Ratios", 
   xlab = "Simulated Risk Ratios", ...)

Arguments

A fitted SemiParBIVProbit object as produced by SemiParBIVProbit().

nm.end

Name of the endogenous variable.

If TRUE then RR calculates the sample RR. If FALSE then it calculates the sample RR for the treated individuals only.

treat

If TRUE then RR calculates the RR using the treated only. If FALSE then it calculates the ratio using the control group. This only makes sense if E = FALSE.

type

This argument can take three values: "naive" (the effect is calculated ignoring the presence of observed and unobserved confounders), "univariate" (the effect is obtained from the univariate probit model which neglects the presen

ind

Binary logical variable. It can be used to calculate the RR for a subset of the data. Note that it does not make sense to use ind when some observations are excluded from the RR calculation (e.g., when using E = FALSE

delta

This option may be available in future, although it will be unreliable at small sample sizes.

n.sim

Number of simulated coefficient vectors from the posterior distribution of the estimated model parameters. This is used when delta = FALSE. It may be increased if more precision is required.

prob.lev

Overall probability of the left and right tails of the RR distribution used for interval calculations.

hd.plot

If TRUE then a plot of the histogram and kernel density estimate of the simulated risk ratios is produced. This can only be produced when delta = FALSE.

prob.plot

For the case of continuous endogenous variable and binary outcome, if TRUE then a plot showing probability that the binary outcome is equal to 1 for each value of the endogenous variable and respective i

main

Title for the plot.

xlab

Title for the x axis.

...

Other graphics parameters to pass on to plotting commands. These are used only when hd.plot = TRUE.

Value

resIt returns three values: lower confidence interval limit, estimated RR and upper interval limit.
prob.levProbability level used.
sim.RRIf delta = FALSE then it returns a vector containing simulated values of the average RR. This is used to calculate intervals.
RR.soIt returns a vector containing the estimated effect for each single observation. This may not be available in some cases.
RatiosFor the case of continuous endogenous variable and binary outcome, it returns a matrix made up of three columns containing the risk ratios for each unit increase in the endogenous variable and respective intervals.
PrFor the case of continuous endogenous variable and binary outcome, it returns a matrix made up of three columns containing the probability that the binary outcome is equal to 1 for each value of the endogenous variable and respective intervals.

Details

RR calculates the sample average risk ratio of the probabilities of positive outcome under treatment (the binary predictor or treatment assumes value 1) and under control (the binary treatment assumes value 0). Posterior simulation is used to obtain a confidence/credible interval. RR works also for the case of continuous endogenous treatment variable.

Examples

Run this code

## see examples for SemiParBIVProbit

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