OR: Causal odds ratio of a binary/continuous/discrete endogenous...

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/OR.r

Description

OR can be used to calculate the causal odds ratio of a binary/continuous/discrete endogenous predictor/treatment, with corresponding interval obtained using posterior simulation.

Usage

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

Arguments

x

A fitted SemiParBIV/copulaReg object.

nm.end

Name of the endogenous variable.

E

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

treat

If TRUE then OR calculates the OR 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 model which neglects the presence of unobserved confounders) and "bivariate" (the effect is obtained from the bivariate model which accounts for observed and unobserved confounders).

ind

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

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 OR distribution used for interval calculations.

length.out

Ddesired length of the sequence to be used when calculating the effect that a continuous/discrete treatment has on a binary outcome.

hd.plot

If TRUE then a plot of the histogram and kernel density estimate of the simulated odds ratios is produced. This can only be produced when binary responses are used.

or.plot

For the case of continuous/discrete endogenous variable and binary outcome, if TRUE then a plot (on the log scale) showing the odd ratios that the binary outcome is equal to 1 for each incremental value of the endogenous variable and respective intervals is produced.

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.

Details

OR calculates the causal odds ratio for a binary/continuous/discrete treatment. Posterior simulation is used to obtain a confidence/credible interval.

Value

prob.lev

Probability level used.

sim.OR

It returns a vector containing simulated values of the average OR. This is used to calculate intervals.

Ratios

For the case of continuous/discrete endogenous treatment and binary outcome, it returns a matrix made up of three columns containing the odds ratios for each incremental value in the endogenous variable and respective intervals.

Author(s)

Maintainer: Giampiero Marra [email protected]

See Also

JRM-package, SemiParBIV, copulaReg

Examples

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## see examples for SemiParBIV and copulaReg

JRM documentation built on July 13, 2017, 5:03 p.m.