n_obs_x

Computes the number of valid (i.e. non-missing) observations for the column/variable of interest.

An easy way to analyze international large-scale assessments and surveys in education or any other dataset that includes replicated weights (Balanced Repeated Replication (BRR) weights, Jackknife replicate weights,...) while also allowing for analysis with multiply imputed variables (plausible values). It supports the estimation of univariate statistics (e.g. mean, variance, standard deviation, quantiles), frequencies, correlation, linear regression and any other model already implemented in R that takes a data frame and weights as parameters. It also includes  options to prepare the results for publication, following the table formatting standards of the Organization for Economic Cooperation and Development (OECD).

Rodolfo Ilizaliturri Lopez

Rrepest

An Analyzer of International Large Scale Assessments in
Education

Rodolfo Ilizaliturri

Francesco Avvisati

Francois Keslair

n_obs_x function

<dl><dt>df</dt>
<dd>(data frame) Data to analyse with lowercase column names.</dd>
<dt>by</dt>
<dd>(string vector) Variable(s) used for tabulating the variable of interest</dd>
<dt>x</dt>
<dd>(string) Variable of interest for which to compute the number of valid (i.e. non-missing) observations</dd>
<dt>svy</dt>
<dd>(string) Survey settings that must be equal to one of the following: ALL, IALS, ICCS, ICILS, IELS,
PBTS, PIAAC, PIRLS, PISA, PISAOOS, PISA2015, SSES, SSES2023, SVY, TALISSCH, TALISTCH, TALISEC_LEADER, TALISEC_STAFF, TIMSS</dd></dl>

Arguments

Number of valid (i.e. non-missing) observations for column/variable x — n_obs_x

<dl>

<dt>df</dt>
<dd>(data frame) Data to analyse with lowercase column names.</dd>


<dt>by</dt>
<dd>(string vector) Variable(s) used for tabulating the variable of interest</dd>


<dt>x</dt>
<dd>(string) Variable of interest for which to compute the number of valid (i.e. non-missing) observations</dd>


<dt>svy</dt>
<dd>(string) Survey settings that must be equal to one of the following: ALL, IALS, ICCS, ICILS, IELS,
PBTS, PIAAC, PIRLS, PISA, PISAOOS, PISA2015, SSES, SSES2023, SVY, TALISSCH, TALISTCH, TALISEC_LEADER, TALISEC_STAFF, TIMSS</dd>

</dl>

n_obs_x: Number of valid (i.e. non-missing) observations for column/variable x

Description

Usage

Value

Arguments

Examples