This function creates LaTeX or HTML regression tables for MCMC Output using
the `texreg`

function from the `texreg`

R package.

mcmcReg( mod, pars = NULL, pointest = "mean", ci = 0.95, hpdi = FALSE, sd = FALSE, pr = FALSE, coefnames = NULL, gof = numeric(0), gofnames = character(0), format = "latex", file, regex = FALSE, ... )

mod | Bayesian model object generated by R2jags, rjags, R2WinBUGS, R2OpenBUGS, MCMCpack, rstan, rstanarm, and brms, or a list of model objects of the same class. |
---|---|

pars | a scalar or vector of the parameters you wish to include in the table.
By default, |

pointest | a character indicating whether to use the mean or median for point estimates in the table. |

ci | a scalar indicating the confidence level of the uncertainty intervals. |

hpdi | a logical indicating whether to use highest posterior density
intervals instead of equal tailed credible intervals to capture uncertainty
(default |

sd | a logical indicating whether to report the standard deviation of
posterior distributions instead of an uncertainty interval
(default |

pr | a logical indicating whether to report the probability that a
coefficient is in the same direction as the point estimate for that
coefficient (default |

coefnames | an optional vector or list of vectors containing parameter
names for each model. If there are multiple models, the list must have the same
number of elements as there are models, and the vector of names in each list
element must match the number of parameters. If not supplied, the function
will use the parameter names in the model object(s). Note that this replaces
the standard |

gof | a named list of goodness of fit statistics, or a list of such lists. |

gofnames | an optional vector or list of vectors containing
goodness of fit statistic names for each model. Like |

format | a character indicating |

file | optional file name to write table to file instead of printing to console. |

regex | use regular expression matching with |

... | optional arguments to |

A formatted regression table in LaTeX or HTML format.

If using `custom.coef.map`

with more than one model, you should rename
the parameters in the model objects to ensure that different parameters with the
same subscript are not conflated by `texreg`

e.g. `beta[1]`

could represent age
in one model and income in another, and `texreg`

would combine the two if you
do not rename `beta[1]`

to more informative names in the model objects.

If `mod`

is a `brmsfit`

object or list of `brmsfit`

objects, note that the
default `brms`

names for coefficients are `b_Intercept`

and `b`

, so both of
these should be included in `par`

if you wish to include the intercept in the
table.

Rob Williams, jayrobwilliams@gmail.com

.old_wd <- setwd(tempdir()) # \donttest{ if (interactive()) { ## simulating data set.seed(123456) b0 <- 0.2 # true value for the intercept b1 <- 0.5 # true value for first beta b2 <- 0.7 # true value for second beta n <- 500 # sample size X1 <- runif(n, -1, 1) X2 <- runif(n, -1, 1) Z <- b0 + b1 * X1 + b2 * X2 pr <- 1 / (1 + exp(-Z)) # inv logit function Y <- rbinom(n, 1, pr) df <- data.frame(cbind(X1, X2, Y)) ## formatting the data for jags datjags <- as.list(df) datjags$N <- length(datjags$Y) ## creating jags model model <- function() { for(i in 1:N){ Y[i] ~ dbern(p[i]) ## Bernoulli distribution of y_i logit(p[i]) <- mu[i] ## Logit link function mu[i] <- b[1] + b[2] * X1[i] + b[3] * X2[i] } for(j in 1:3){ b[j] ~ dnorm(0, 0.001) ## Use a coefficient vector for simplicity } } params <- c("b") inits1 <- list("b" = rep(0, 3)) inits2 <- list("b" = rep(0, 3)) inits <- list(inits1, inits2) ## fitting the model with R2jags set.seed(123) fit <- R2jags::jags(data = datjags, inits = inits, parameters.to.save = params, n.chains = 2, n.iter = 2000, n.burnin = 1000, model.file = model) ## generating regression table with all parameters mcmcReg(fit) ## generating regression table with only betas and custom coefficent names mcmcReg(fit, pars = c('b'), coefnames = c('Variable 1', 'Variable 2', 'Variable 3'), regex = TRUE) ## generating regression tables with all betas and custom names mcmcReg(fit, coefnames = c('Variable 1', 'Variable 2', 'Variable 3', 'deviance')) } # } setwd(.old_wd)