### Search Results:

Showing results 1 to 10 of 469.

##### Function calibVars[simPop v1.2.0]
keywords
survey
title
Construct a matrix of binary variables for calibration
description
Construct a matrix of binary variables for calibration of sample weights according to known marginal population totals. The following methods are implemented: calibVars.default(x) calibVars.matrix(x) calibVars.matrix(x) calibVars.data.frame(x)
##### Function logi.hist.plot2[logihist v1.0]
keywords
~survey
title
Plot logistic regression
description
Plot combined graphs for logistic regressions
##### Function comb.samples[StatMatch v1.4.0]
keywords
survey
title
Statistical Matching of data from complex sample surveys
description
This function permits to cross-tabulate two categorical variables, Y and Z, observed separately in two independent surveys (Y is collected in survey A and Z is collected in survey B) carried out on the same target population. The two surveys share a number of common variables X. When it is available a third survey C, carried on the same population, in which both Y and Z are collected, these data are used as a source of auxiliary information. The statistical matching is performed by carrying out calibration of the survey weights, as suggested in Renssen (1998). It is possible also to use the function to derive the estimates that a unit falls in one of the categories of the target variable (estimation are based on Liner Probability Models and are obtained as a by-product of the Renssen's method).
##### Function harmonize.x[StatMatch v1.4.0]
keywords
survey
title
Harmonizes the marginal (joint) distribution of a set of variables observed independently in two sample surveys referred to the same target population
description
This function permits to harmonize the marginal or the joint distribution of a set of variables observed independently in two sample surveys carried out on the same target population. This harmonization is carried out by using the calibration of the survey weights of the sample units in both the surveys according to the procedure suggested by Renssen (1998).
##### Function varstsi[optimStrat v2.1]
keywords
survey
title
Variance of STSI Sampling with the HT Estimator
description
Compute the design variance of the Horvitz-Thompson estimator of the total of y under Stratified Simple Random Sampling, where strata are indicated by stratum and the sample sizes by stratum are given by nh.
##### Function expmse[optimStrat v2.1]
keywords
survey
title
Anticipated Mean Squared Error
description
Compute the anticipated Mean Squared Error of five sampling strategies.
##### Function varpips[optimStrat v2.1]
keywords
survey
title
Variance of Pareto PIps Sampling with the HT Estimator
description
Compute the design variance of the Horvitz-Thompson estimator of the total of y under Pareto probability proportional-to-size Sampling, where the size variable is indicated by x and the sample size is n.
##### Function varstsipos[optimStrat v2.1]
keywords
survey
title
Design variance of a STSI--pos sampling strategy.
description
Compute the design variance of the poststratified estimator of the total of y under Stratified Simple Random Sampling, where strata are indicated by stratum and the sample of size n is allocated using Neyman allocation with respect to x.
##### Function simulatey[optimStrat v2.1]
keywords
survey
title
Simulate the Study Variable
description
Simulate values for the study variable based on the auxiliary variable x and the parameters of a superpopulation model.
##### Function stratify[optimStrat v2.1]
keywords
survey
title
Stratification of an Auxiliary Variable
description
Stratify the auxiliary variable x into H strata using the cum-sqrt-rule.