coef.lframe | R Documentation |
Extract the coefficients from the estimated cross-sectional measures
## S3 method for class 'lframe'
coef(object, ...)
object |
a "lframe"-class object |
... |
other arguments. |
The coef
method for "lframe"-class objects find the point estimates from the
different AF measures. 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.)
Coefficients extracted from the model lframe
object.
Ignacio Girela
confint
, and summary
methods, and mpitb.est
function.
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))
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