confint.lframe {mpitbR}

Extract the confidence intervals from the the estimated cross-sectional measures

Description

Extract the confidence intervals from the the estimated cross-sectional measures

Usage

## S3 method for class 'lframe'
confint(object, parm = "coefficient", level = 0.95, ...)

Arguments

object

a "lframe"-class object

parm

"coefficient". Confidence intervals are only available for AF measure point estimates.

level

the confidence level required.

...

additional argument(s) for methods.

Details

The confint method for "lframe"-class objects find the confidence intervals from the different AF measures estimates data frame. This method work for only one measure c("M0","H","A","hd","hdk") (Note that contribution measure do no have confidence intervals). Then, user should subset the data frame with the estimates by the chosen measure (including other preferred categories, i.e., poverty cut-off, subgroup, etc.)

Value

Confidence intervals extracted from the model lframe object.

Author(s)

Ignacio Girela

See Also

coef, and summary methods, and mpitb.est function.

Examples

library(mpitbR)

data <- subset(syn_cdta)
data <- na.omit(data)

svydata <- survey::svydesign(id=~psu, weights = ~weight, strata = ~stratum, data = data)

indicators <- list(d1 = c("d_nutr","d_cm"),
                   d2 = c("d_satt","d_educ"),
                   d3 = c("d_elct","d_sani","d_wtr","d_hsg","d_ckfl","d_asst"))

# Specify mpitb project
set <- mpitb.set(svydata, indicators = indicators, name = "myname", desc = "pref. desc")

# Estimate the cross-sectional MPI and compare non-annualized changes over time
est <- mpitb.est(set, klist = c(33), measures = "M0", indmeasures = NULL,
                 tvar = "t", cotmeasures = "M0",
                 weights = "equal", over = c("area"))

coef(subset(est$lframe, measure == "M0" & t == 1))
confint(subset(est$lframe, measure == "M0" & t == 1))
summary(subset(est$lframe, measure == "M0" & t == 1))

coef(subset(est$cotframe, measure == "M0"))
confint(subset(est$cotframe, measure == "M0"))
summary(subset(est$cotframe, measure == "M0" & ctype == "abs" & ann == 0 & k == 33))