logRespRatio {ARPobservation}

Calculate log-response ratio, variance, and confidence interval

Description

Estimates the log-response ratio (with or without bias correction), the variance of the log-response ratio, and the confidence interval for a given confidence level.

Usage

logRespRatio(
  observations,
  phase,
  base_level,
  conf_level = 0.95,
  bias_correct = TRUE,
  exponentiate = FALSE
)

Arguments

observations

Vector of observations

phase

Factor or vector indicating levels of the PIR measurements.

base_level

a character string or value indicating the name of the baseline level.

conf_level

Desired coverage rate of the calculated confidence interval. Default is .95.

bias_correct

Logical value indicating if the bias-corrected log-response ratio should be used. Default is TRUE

exponentiate

Logical value indicating if the log-response ratio should be exponentiated.

Details

The observations vector can be in any order corresponding to the factor or vector phase. The levels of phase can be any two levels, such as "A" and "B", "base" and "treat", or "0" and "1". If there are more than two levels in phase this function will not work. A value for base_level must be specified - if it is a character string it is case sensitive. If exponentiate = TRUE, the log-ratio and the confidence interval will be exponentiated, but the variance will be excluded from the output.

Value

If exponentiate = FALSE, a list with three named entries. The first entry, lRR, is the estimated log-response ratio. The second entry, V_lRR, is the estimated variance of the log-response ratio. The third entry, CI, is a vector containing the endpoints of a confidence interval of conf_level coverage rate.

If exponentiate = TRUE, a list with two named entries. The first entry, RR, is the estimated response ratio. The second entry, CI, is a vector containing the endpoints of a confidence interval of conf_level coverage rate.

Author(s)

Daniel Swan <[e-mail]>

Examples

# Estimate the log response ratio and its variance for Carl from Moes dataset
data(Moes)
with(subset(Moes, Case == "Carl"),
logRespRatio(observations = outcome, phase = Phase, base_level = "No Choice"))