add.point.est: Adds point estimates to samples.

In david-borchers/sampling: Module MT4608 Sampling Theory Practical Package

Adds point estimates to samples.

Description

This function calculates point estimates of population mean, total or proportion from an object of class 'sample' or 'samples.population' and adds it to the sample in a column named "point.est".

Usage

  add.point.est(dat,type="ybar",cond=NULL)

Arguments

dat	Object of class 'sample' or 'samples.population'.
type	Type of point estimate. Valid types are ybarsample mean ybar.totsample total ybar.ppnsample proportion strat.meanstratified sample mean strat.totstratified sample totatl strat.ppnstratified sample proportion ratio.meanratio estimate of mean ratio.totratio estimate of toatal ratio.ppnratio estimate of proportion strat.ratiostratified ratio estimate of mean strat.ratio.totstratified ratio estimate of total strat.ratio.ppnstratified ratio estimate of proportion regr.meanregression estimate of mean regr.totregression estimate of total regr.ppnregression estimate of proportion strat.regrstratified regression estimate of mean strat.regr.totstratified regression estimate of total strat.regr.ppnstratified regression estimate of proportion diffr.meandifference estimate of mean diffr.totdifference estimate of total diffr.ppndifference estimate of proportion strat.diffrstratified difference estimate of mean strat.diffr.totstratified difference estimate of total strat.diffr.ppnstratified difference estimate of proportion clust.meancluster estimate of mean from mean of cluster totals clust.totcluster estimate of mean from total of cluster totals clust.ppncluster estimate of proportion from mean of cluster totals clust.r.meancluster ratio estimate of mean clust.r.totcluster ratio estimate of total clust.r.ppncluster ratio estimate of proportion
cond	Condition to use when calculation proportions. Character of form "<logical operator><value>", where <value> is a valid value for the response variable (y) and <logical operator> is one of the following: "<"if you want the proportion of response values less than <value> ">"if you want the proportion of response values greater than <value> "<="if you want the proportion of response values less than or equal to <value> ">="if you want the proportion of response values greater than or equal to <value> "=="if you want the proportion of response values equal to <value> "!="if you want the proportion of response values not equal to <value>

Details

Returns object identical to 'dat' but with a new element called "point.est" containing the point estimate(s) of the appropriate type.

Value

Returns data frame identical to 'dat' but with a new column called "point.est" containing the point estimate(s) of the appropriate type.

See Also

point.est, var.est, add.var.est, ci.est, add.ci.est

Examples

  data(barnett) # get barnett data
  
  # All samples total weight of class from srs:
  samp.dbn<-take.sample(barnett,y.name="weight",n=23,take.all=TRUE)
  # estimate total
  samp.dbn<-add.point.est(samp.dbn,type="ybar.tot")
  
  # proportion of class with weight more than 15, from srs:
  samp.dbn<-take.sample(barnett,y.name="weight",n=23,take.all=TRUE)
  # estimate total
  samp.dbn<-add.point.est(samp.dbn,type="ybar.ppn",cond=">15")
  
  # Stratified mean
  # Define 4 strata based on weight, with 10 lb interval widths:
  
    strat.barnett<-define.subunit(barnett,aux.name="weight",breaks=c(0,10,20,30,40),
                                    type="strat")
  # take stratified sample
  
    samp.dbn<-take.sample(strat.barnett,y.name="height",type="strat",n=c(2,9,7,3),ta
                            ke.all=TRUE)
  # estimate mean height using stratified estimator
  samp.dbn<-add.point.est(samp.dbn,type="strat.mean")
  
  # Cluster mean
  # Define 5 clusters based on weight:
  clust.barnett<-define.subunit(barnett,aux.name="weight",
                                breaks=c(0,10,15,20,25,30,40),type="clust")
  # take cluster sample of size 3
  
    samp.dbn<-take.sample(clust.barnett,y.name="height",type="clust",m=3,take.all=TR
                            UE)
  # estimate mean height using cluster estimator
  samp.dbn<-add.point.est(samp.dbn,type="clust.mean")
  
  # Ratio estimator
  # take srs of size 6, with weight as auxiliary variable:
  
    samp.dbn<-take.sample(barnett,y.name="height",aux.name="weight",type="srs",n=23,
                            take.all=TRUE)
  # estimate mean height using cluster estimator
  samp.dbn<-add.point.est(samp.dbn,type="ratio.mean")
  

david-borchers/sampling documentation built on Sept. 17, 2022, 7:54 a.m.