Prepare Questionnaire Data for Analysis

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Documentation for package ‘quest’ version 0.2.0

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A B C D F G I L M N P Q R S T U V W misc

quest-package Pre-processing Questionnaire Data

-- A --

add_sig Add Significance Symbols to a (Atomic) Vector, Matrix, or Array
add_sig_cor Add Significance Symbols to a Correlation Matrix
agg Aggregate an Atomic Vector by Group
aggs Aggregate Data by Group
agg_dfm Data Information by Group
amd_bi Amount of Missing Data - Bivariate (Pairwise Deletion)
amd_multi Amount of Missing Data - Multivariate (Listwise Deletion)
amd_uni Amount of Missing Data - Univariate
auto_by Autoregressive Coefficient by Group
ave_dfm Repeated Group Statistics for a Data-Frame

-- B --

boot_ci Bootstrapped Confidence Intervals from a Matrix of Coefficients
by2 Apply a Function to Data by Group

-- C --

center Centering and/or Standardizing a Numeric Vector
centers Centering and/or Standardizing Numeric Data
centers_by Centering and/or Standardizing Numeric Data by Group
center_by Centering and/or Standardizing a Numeric Vector by Group
change Change Score from a Numeric Vector
changes Change Scores from Numeric Data
changes_by Change Scores from Numeric Data by Group
change_by Change Scores from a Numeric Vector by Group
colMeans_if Column Means Conditional on Frequency of Observed Values
colNA Frequency of Missing Values by Column
colSums_if Column Sums Conditional on Frequency of Observed Values
composite Composite Reliability of a Score
composites Composite Reliability of Multiple Scores
confint2 Confidence Intervals from Statistical Information
confint2.boot Bootstrapped Confidence Intervals from a 'boot' Object
confint2.default Confidence Intervals from Parameter Estimates and Standard Errors
corp Bivariate Correlations with Significant Symbols
corp_by Bivariate Correlations with Significant Symbols by Group
corp_miss Point-biserial Correlations of Missingness With Significant Symbols
corp_ml 'corp_ml' decomposes correlations from multilevel data into within-group and between-group correlations as well as adds significance symbols to the end of each value. The workhorse of the function is 'statsBy'. 'corp_ml' is simply a combination of 'cor_ml' and 'add_sig_cor'.
cor_by Correlation Matrix by Group
cor_miss Point-biserial Correlations of Missingness
cor_ml Multilevel Correlation Matrices
covs_test Covariances Test of Significance
cronbach Cronbach's Alpha of a Set of Variables/Items
cronbachs Cronbach's Alpha for Multiple Sets of Variables/Items

-- D --

decompose Decompose a Numeric Vector by Group
decomposes Decompose Numeric Data by Group
deff Design Effect from Multilevel Numeric Vector
deffs Design Effects from Multilevel Numeric Data
describe_ml Multilevel Descriptive Statistics
dum2nom Dummy Variables to a Nominal Variable

-- F --

freq Univariate Frequency Table
freqs Multiple Univariate Frequency Tables
freqs_by Multiple Univariate Frequency Tables
freq_by Univariate Frequency Table By Group

-- G --

gtheory Generalizability Theory Reliability of a Score
gtheorys Generalizability Theory Reliability of Multiple Scores
gtheorys_ml Generalizability Theory Reliability of Multiple Multilevel Scores
gtheory_ml Generalizability Theory Reliability of a Multilevel Score

-- I --

iccs_11 Intraclass Correlation for Multiple Variables for Multilevel Analysis: ICC(1,1)
icc_11 Intraclass Correlation for Multilevel Analysis: ICC(1,1)
icc_all_by All Six Intraclass Correlations by Group

-- L --

lengths_by Length of Data Columns by Group
length_by Length of a (Atomic) Vector by Group
long2wide Reshape Multiple Scores From Long to Wide

-- M --

make.dummy Make Dummy Columns
make.dumNA Make Dummy Columns For Missing Data.
make.fun_if Make a Function Conditional on Frequency of Observed Values
make.latent Make Model Syntax for a Latent Factor in Lavaan
make.product Make Product Terms (e.g., interactions)
means_change Mean Changes Across Two Timepoints For Multiple PrePost Pairs of Variables (dependent two-samples t-tests)
means_compare Mean differences for multiple variables across 3+ independent groups (one-way ANOVAs)
means_diff Mean differences across two independent groups (independent two-samples t-tests)
means_test Test for Multiple Sample Means Against Mu (one-sample t-tests)
mean_change Mean Change Across Two Timepoints (dependent two-samples t-test)
mean_compare Mean differences for a single variable across 3+ independent groups (one-way ANOVA)
mean_diff Mean difference across two independent groups (independent two-samples t-test)
mean_if Mean Conditional on Minimum Frequency of Observed Values
mean_test Test for Sample Mean Against Mu (one-sample t-test)
mode2 Statistical Mode of a Numeric Vector

-- N --

ncases Number of Cases in Data
ncases_by Number of Cases in Data by Group
ncases_desc Describe Number of Cases in Data by Group
ncases_ml Multilevel Number of Cases
ngrp Number of Groups in Data
nhst Null Hypothesis Significance Testing
nom2dum Nominal Variable to Dummy Variables
nrow_by Number of Rows in Data by Group
nrow_ml Multilevel Number of Rows
n_compare Test for Equal Frequency of Values (chi-square test of goodness of fit)

-- P --

partial.cases Find Partial Cases
pomp Recode a Numeric Vector to Percentage of Maximum Possible (POMP) Units
pomps Recode Numeric Data to Percentage of Maximum Possible (POMP) Units
props_compare Proportion Comparisons for Multiple Variables across 3+ Independent Groups (Chi-square Tests of Independence)
props_diff Proportion Difference of Multiple Variables Across Two Independent Groups (Chi-square Tests of Independence)
props_test Test for Multiple Sample Proportion Against Pi (Chi-square Tests of Goodness of Fit)
prop_compare Proportion Comparisons for a Single Variable across 3+ Independent Groups (Chi-square Test of Independence)
prop_diff Proportion Difference for a Single Variable across Two Independent Groups (Chi-square Test of Independence)
prop_test Test for Sample Proportion Against Pi (chi-square test of goodness of fit)

-- Q --

quest Pre-processing Questionnaire Data

-- R --

recode2other Recode Unique Values in a Character Vector to 0ther (or NA)
recodes Recode Data
renames Rename Data Columns from a Codebook
reorders Reorder Levels of Factor Data
revalid Recode Invalid Values from a Vector
revalids Recode Invalid Values from Data
reverse Reverse Code a Numeric Vector
reverses Reverse Code Numeric Data
rowMeans_if Row Means Conditional on Frequency of Observed Values
rowNA Frequency of Missing Values by Row
rowsNA Frequency of Multiple Sets of Missing Values by Row
rowSums_if Row Sums Conditional on Frequency of Observed Values

-- S --

score Observed Unweighted Scoring of a Set of Variables/Items
scores Observed Unweighted Scoring of Multiple Sets of Variables/Items
shift Shift a Vector (i.e., lag/lead)
shifts Shift Data (i.e., lag/lead)
shifts_by Shift Data (i.e., lag/lead) by Group
shift_by Shift a Vector (i.e., lag/lead) by Group
summary_ucfa Summary of a Unidimensional Confirmatory Factor Analysis
sum_if Sum Conditional on Minimum Frequency of Observed Values

-- T --

tapply2 Apply a Function to a (Atomic) Vector by Group

-- U --

ucfa Unidimensional Confirmatory Factor Analysis

-- V --

valids_test Test for Invalid Elements in Data
valid_test Test for Invalid Elements in a Vector
vecNA Frequency of Missing Values in a Vector

-- W --

wide2long Reshape Multiple Sets of Variables From Wide to Long
winsor Winsorize a Numeric Vector
winsors Winsorize Numeric Data

-- misc --

.cronbach Bootstrap Function for 'cronbach()' Function
.cronbachs Bootstrap Function for 'cronbachs()' Function
.gtheory Bootstrap Function for 'gtheory()' Function
.gtheorys Bootstrap Function for 'gtheorys()' Function