ci.ratio.mape2: Confidence interval for a ratio of mean absolute prediction...

In statpsych: Statistical Methods for Psychologists

Confidence interval for a ratio of mean absolute prediction errors in a 2-group design

Description

Computes a confidence interval for a ratio of population mean absolute prediction errors from a general linear model in two independent groups. The number of predictor variables can differ across groups and the two models can be non-nested. This function requires a vector of estimated residuals from each group. This function does not assume zero excess kurtosis but does assume symmetry in the population prediction errors for the two models.

Usage

ci.ratio.mape2(alpha, res1, res2, s1, s2)

Arguments

alpha	alpha level for 1-alpha confidence
res1	vector of residuals from group 1
res2	vector of residuals from group 2
s1	number of predictor variables used in group 1
s2	number of predictor variables used in group 2

Value

Returns a 1-row matrix. The columns are:

• MAPE1 - bias adjusted mean absolute prediction error for group 1

• MAPE2 - bias adjusted mean absolute prediction error for group 2

• MAPE1/MAPE2 - ratio of bias adjusted mean absolute prediction errors

• LL - lower limit of the confidence interval

• UL - upper limit of the confidence interval

Examples

res1 <- c(-2.70, -2.69, -1.32, 1.02, 1.23, -1.46, 2.21, -2.10, 2.56, -3.02
        -1.55, 1.46, 4.02, 2.34)
res2 <- c(-0.71, -0.89, 0.72, -0.35, 0.33 -0.92, 2.37, 0.51, 0.68, -0.85,
        -0.15, 0.77, -1.52, 0.89, -0.29, -0.23, -0.94, 0.93, -0.31 -0.04)
ci.ratio.mape2(.05, res1, res2, 1, 1)

# Should return:
#   MAPE1     MAPE2 MAPE1/MAPE2       LL       UL
# 2.58087 0.8327273    3.099298 1.917003 5.010761
 

statpsych documentation built on Sept. 11, 2024, 7:42 p.m.