Provide additional information on the response variable in brms models, such as censoring, truncation, or known measurement error.
resp_se(x, sigma = FALSE)resp_weights(x, scale = FALSE)
resp_trials(x)
resp_thres(x, gr = NA)
resp_cat(x)
resp_dec(x)
resp_cens(x, y2 = NA)
resp_trunc(lb = -Inf, ub = Inf)
resp_mi(sdy = NA)
resp_rate(denom)
resp_subset(x)
resp_vreal(...)
resp_vint(...)
A vector; usually a variable defined in the data. Allowed values
depend on the function: resp_se
and resp_weights
require
positive numeric values. resp_trials
, resp_thres
, and
resp_cat
require positive integers. resp_dec
requires
0
and 1
, or alternatively 'lower'
and 'upper'
.
resp_subset
requires 0
and 1
, or alternatively
FALSE
and TRUE
. resp_cens
requires 'left'
,
'none'
, 'right'
, and 'interval'
(or equivalently
-1
, 0
, 1
, and 2
) to indicate left, no, right,
or interval censoring.
Logical; Indicates whether the residual standard deviation
parameter sigma
should be included in addition to the known
measurement error. Defaults to FALSE
for backwards compatibility,
but setting it to TRUE
is usually the better choice.
Logical; Indicates whether weights should be scaled
so that the average weight equals one. Defaults to FALSE
.
A vector of grouping indicators.
A vector specifying the upper bounds in interval censoring.
Will be ignored for non-interval censored observations. However, it
should NOT be NA
even for non-interval censored observations to
avoid accidental exclusion of these observations.
A numeric vector or single numeric value specifying the lower truncation bound.
A numeric vector or single numeric value specifying the upper truncation bound.
Optional known measurement error of the response treated as standard deviation. If specified, handles measurement error and (completely) missing values at the same time using the plausible-values-technique.
A vector of positive numeric values specifying the denominator values from which the response rates are computed.
For resp_vreal
, vectors of real values.
For resp_vint
, vectors of integer values.
A list of additional response information to be processed further by brms.
These functions are almost solely useful when
called in formulas passed to the brms package.
Within formulas, the resp_
prefix may be omitted.
More information is given in the 'Details' section
of brmsformula
.
# NOT RUN {
## Random effects meta-analysis
nstudies <- 20
true_effects <- rnorm(nstudies, 0.5, 0.2)
sei <- runif(nstudies, 0.05, 0.3)
outcomes <- rnorm(nstudies, true_effects, sei)
data1 <- data.frame(outcomes, sei)
fit1 <- brm(outcomes | se(sei, sigma = TRUE) ~ 1,
data = data1)
summary(fit1)
## Probit regression using the binomial family
n <- sample(1:10, 100, TRUE) # number of trials
success <- rbinom(100, size = n, prob = 0.4)
x <- rnorm(100)
data2 <- data.frame(n, success, x)
fit2 <- brm(success | trials(n) ~ x, data = data2,
family = binomial("probit"))
summary(fit2)
## Survival regression modeling the time between the first
## and second recurrence of an infection in kidney patients.
fit3 <- brm(time | cens(censored) ~ age * sex + disease + (1|patient),
data = kidney, family = lognormal())
summary(fit3)
## Poisson model with truncated counts
fit4 <- brm(count | trunc(ub = 104) ~ zBase * Trt,
data = epilepsy, family = poisson())
summary(fit4)
# }
# NOT RUN {
# }
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