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

In GJRM: Generalised Joint Regression Modelling

Causal odds ratio of a binary/continuous/discrete endogenous variable

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

OR(x, nm.end, E = TRUE, treat = TRUE, type = "joint", 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 gjrm 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 "joint" (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 [e-mail]

See Also

GJRM-package, gjrm

GJRM documentation built on July 9, 2023, 7:15 p.m.