help pvalso see: pvtest -------------------------------------------------------------------------------

Title

pv-- Estimation with plausible values

Syntax

pv[indepvars] [if] [in] [weight],pv(varlist)[options]

optionsDescription ------------------------------------------------------------------------- Mainpv(varlist)plausible value estimates of the dependent variablecmd("command")estimation command to estimate the statistic, default is regresscmdops("options")options for the estimation commandVCE BRR (PISA)

brrspecifies Balanced Repeated Replication (BRR) be used for VCErw(varlist)BRR replicate weights to be usedfays(real)Fay's adjustmentVCE JRR (TIMSS PIRLS)

jrrspecifies Jackknifed Repeated Replication (JRR) be used for VCEjkzone(varname)Sampling zone variablejkrep(varname)Zone replicate weight variableVCE Bootstrap

bsspecifies that Stata's bootstrap command be used for VCEbsops("options")options for Stata's bootstrap commandVCE Aggregation

pisaspecifies PISA's formula for aggregating VCE be usedtimssspecifies TIMSS formula for aggregating VCE be usedpirlsspecifies PIRLS formula for aggregating VCE be used -------------------------------------------------------------------------

fweights,iweights,aweights, orpweights are required; see weight. See pvtest for post estimation hypothesis testing. The default VCE utilizes the VCE reported by the command for each plausible value.

Description

pvestimates statistics when there are multiple estimates of the dependent variable (which are sometimes referred to as plausible values) by calculating the statistics for each estimate of the dependent variable and then calculating their average. This program can be used with any statistics estimation commands that accepts weights includingregress,qreg,logit,mean, etc. It is specially (but not exclusively) designed to be used with the PISA, TIMSS and PIRLS student achievement datasets.The VCE can be calculated in one of four ways. The default is to use an aggregation of the VCEs for each plausible value which is reported by the specified stata command. Alternatively, Balanced Repeated Replication (used with PISA), Jackknifed Repeated Replication (used with TIMSS and PIRLS), or bootstrapping can be used.

See the Formulas section below.

Options+------+ ----+ Main +-------------------------------------------------------------

pv(varlist)the variable list of plausible values or estimates of the dependent variable.

cmd("command")specifies the name of estimation command to be used. Estimation commands must allow weights, and they must output their estimates to e(b).

cmdops("options")options to be specified for the estimation command.

+---------+ ----+ VCE BRR +----------------------------------------------------------

brrspecifies that Balanced Repeated Replication be used for estimating the sampling variance.

rw(varlist)specifies the variable list of replicate weights to be used. In PISA 2000, 2003, and 2006 these variables are w_fstr1 - w_fstr80.

fays(real)is the Fay's adjustment. In PISA 2000, 2003, and 2006 this is 0.5.+---------+ ----+ VCE JRR +----------------------------------------------------------

jrrspecifies that Jackknifed Repeated Replication be used for estimating the sampling variance.

jkzone(varname)is a categorical variable that specifies the sampling zone; for TIMSS and PIRLS this variable is jkzone.

jkrep(varname)is a binary variable that specifies the observation's weighting within its zone; for TIMSS and PIRLS, this variable is jkrep.+---------------+ ----+ VCE Bootstrap +----------------------------------------------------

bsspecifies that bootstrapping should be used to calculate the sampling variance. The expression list is assumed to be e(b); as a result, the user can only control the options.

bsops("options")specifies any bootstrapping options; seebootstrap.+-----------------+ ----+ VCE Aggregation +--------------------------------------------------

pisatells the program to aggregate the VCE according to the formula on page 79 of OECD (2005a); this is the default.

timsstells the program to aggregate the VCE according to the formula on 2-52 of IEA (2005).

pirlstells the program to aggregate the VCE according to the formula on 2-52 of IEA (2005); see the description of formulas below.

ExamplesEstimating statistics with PISA

. pv stratio propqual [aw=w_fstuwt], pv(pv*math) cmd("reg") brrrw(w_fstr*) fays(0.5)

. pvtest stratio=propqual

. pv stratio [aw=w_fstuwt], pv(pv*math) cmd("qreg") brr rw(w_fstr*)fays(0.5)

. pv stratio [aw=w_fstuwt], pv(pv*math) cmd("mean") brr rw(w_fstr*)fays(0.5)

. pv stratio [aw=w_fstuwt], pv(pv*math) bs bsops("reps(80)str(stratum) cl(schoolid)")Estimating statistics with TIMSS and PIRLS

. pv [aw=tchwgt], cmd("mean") pv(asrrea*) jkzone(jkzone) jkrep(jkrep)jrr timss

. pv asbgsex [aw=tchwgt], pv(asrrea*) jkzone(jkzone) jkrep(jkrep) jrrtimssEstimating statistics with BRR VCE with a regular dependent variable

. pv stratio [aw=w_fstuwt], pv(propqual) cmd("reg") brr rw(w_fstr*)fays(0.5)

FormulasTo calculate statistics that are functions of plausible value estimates of a variable, the statistic is calculated for each plausible value and then averaged. See OECD (2005a), page 79 for the formula used in this program.

To calculate the standard error of statistics that are functions of plausible value estimates of a variable average sampling variance of the statistic for each plausible value combined with the variation among the estimated statistics for each plausible value.

By specifying the

pisaoption, the formula used to calculate the standard error can be found on page 79 of OECD (2005a). By specifying thetimssorpirlsoption, the formula can be found on page 2-52 of IEA (2005).The formula for calculating the VCE for statistics using BRR is taken from page 51 of OECD (2005a) while the formula used for calculating the VCE for JRR is from page 2-50 in IEA (2005).

The formula for calculating the parameter for the t-distribution of the ratio of a statistic and its standard error is on page 131 of OECD (2005b).

ReferencesLauzon D. (2004), "Variance estimation with plausible value achievement data: Two STATA programs for use with YITS/PISA data",

Information andTechnical Bulletin, Statistics Canada, OttawaOECD (2005a),

PISA 2003 Data Analysis Manual, OECD, ParisOECD (2005b),

PISA 2003 Technical Report, OECD, ParisIEA (2005),

TIMSS 2003 User Guide for the International Database, IEA, Chestnut Hill, MA

AuthorKevin Macdonald is a consultant with the Education Team in the World Bank's Human Development Network and has a master's degree in economics from the University of British Columbia in Vancouver, Canada. Please send questions, comments or complaints to kadmacdonald@gmail.com.

The command syntax and display for this program was inspired by Lauzon (2004).

Also see

pvtest

VersionLast updated 2008-09-05