rec.mean.var: rec.mean.var

In DACF: Data Analysis with Ceiling and/or Floor Data

rec.mean.var

Description

recover mean and variance of the data with ceiling/floor effects

Usage

rec.mean.var(y, flr, ceil)

Arguments

y	a (non-empty) numeric vector of data with ceiling/floor effects
flr	a (non-empty) numeric value of the floor threshold (e.g., the minimum score of the measurement scale)
ceil	a (non-empty) numeric value of the ceiling threshold (e.g., the maximum score of the measurement scale)

Value

ceiling.percentage	the percentage of ceiling values in the data
floor.percentage	the percentage of floor values in the data
est.mean	estimated mean of the true scores
est.var	estimated variance of the true scores

Examples

# simulate normally distributed true scores
x=rnorm(1000,2,4)
mean(x); var(x)
# induce 20% floor effects
# and estimate the true mean variance from the floor data
x.f=induce.cfe(.2,0,x)
rec.mean.var(x.f, flr=min(x.f), ceil=max(x.f))
# induce 20% ceiling effects
# and estimate the true mean and variance from the ceiling data
x.c=induce.cfe(0,.2,x)
rec.mean.var(x.c, flr=min(x.c), ceil=max(x.c))
# induce 20% and 10% of floor and ceiling effects, respectively
# and estimate the true mean and variance from the data with floor and ceiling effects
x.cf=induce.cfe(.2,.1,x)
rec.mean.var(x.cf, flr=min(x.cf), ceil=max(x.cf))

DACF documentation built on July 17, 2026, 1:07 a.m.