# Using R on LISSY

This page explains the special methods used to load *LIS and LWS data* in *R* and generate output, and documents the add-on packages currently available on the system.

## Loading Data

Data is read into the workspace using the *read.LIS* function, which has one required argument and three optional arguments. It works as follows:

## Usage

read.LIS(ccyyuu, labels=TRUE, vars=NULL, subset=NULL)

## Arguments

ccyyuu | A string or vector of strings containing dataset identifiers, indicating which datasets to load. For the formatting of this identifier, see Details. |

labels | A logical value indicating whether to use the value labels for categorical variables. If TRUE, creates a factor from the labels. If FALSE, uses the numeric codes. |

subset | An optional string specifying a subset of observations to be return. By default, all observations are returned. |

vars | An optional vector of variables to be loaded. By default, all variables are returned. |

## Details

The format of *ccyyuu* is a country and year code followed by a one-letter code used to identify the specific type of dataset within each database:

LIS dataset |
‘h’ or ‘p’ for household or person file | e.g. “lu04h”, “us10p” |

LWS dataset |
‘h’, ‘p’ or ‘r’ for household, person or implicate file | e.g. “ca05h”, “us10p” or “us10r” |

If a vector of multiple dataset identifiers is provided, the datasets will be concatenated and returned as a single “stacked” data frame. Attempting to simultaneously retrieve two datasets containing different variables (e.g., a household and a person file) will cause an error, because such incompatible datasets cannot be stacked on top of one another.

See Examples for code that retrieves the household and person files separately and then generates a merged file, with household data appended to individual records.

When labels is set to FALSE, the value labels will still be stored in the attributes of the data frame, in the named list attribute “label.table”.

## Value

A data frame with attributes. See the documentation for read.dta13 for more information.

## Examples

# Load the household file for Luxembourg 2010ds <- read.LIS('lu10h')# Load the person file for Luxembourg 2010, numeric codes onlyds <- read.LIS('lu10p', labels=FALSE) print(table(ds$educ)) print(attributes(ds)$label.table$educ)# Load a combined dataset for Luxembourg 2004 and 2010, containing only the dataset name, weights, and disposable household income, for households containing children under age 18.ds <- read.LIS(c('lu04h','lu10h'), vars=c('dname','hwgt','dhi'), subset="nhhmem17>0")# Load and merge the household and person files for Luxembourg 2010dsh <- read.LIS('lu10h') dsp <- read.LIS('lu10p') ds <- merge(dsp, dsh, by="hid")

## Producing Output

Because of LIS security procedures, you may need to make small modifications to your code in order to produce output. In order to ensure that it will appear in the log file, you must explicitly *print()* an object, for example:

print(table(x))

In addition, the printing of objects of class data.frame has been disabled.

## Add-on packages

The *R* installation on *LISSY* includes all the packages that are included in base *R*, as well as all the recommended packages. In addition, the packages listed below are available and can be loaded using functions such as

library()

or

require()

If you would like to request a package that is not currently installed, please inform User Support and we will consider it for inclusion in a future system update.

Package |
Version |
Title |
---|---|---|

abind | 1.4-5 | Combine Multidimensional Arrays |

acepack | 1.4.1 | ACE and AVAS for Selecting Multiple Regression Transformations |

arm | 1.10-1 | Data Analysis Using Regression and Multilevel/Hierarchical Models |

assertthat | 0.2.0 | Easy Pre and Post Assertions |

backports | 1.1.3 | Reimplementations of Functions Introduced Since R-3.0.0 |

base64enc | 0.1-3 | Tools for base64 encoding |

bayesplot | 1.6.0 | Plotting for Bayesian Models |

BH | 1.69.0-1 | Boost C++ Header Files |

bibtex | 0.4.2 | Bibtex Parser |

bindr | 0.1.1 | Parametrized Active Bindings |

bindrcpp | 0.2.2 | An 'Rcpp' Interface to Active Bindings |

blme | 1.0-4 | Bayesian Linear Mixed-Effects Models |

broom | 0.5.1 | Convert Statistical Analysis Objects into Tidy Tibbles |

carData | 3.0-2 | Companion to Applied Regression Data Sets |

caret | 6.0-81 | Classification and Regression Training |

checkmate | 1.9.1 | Fast and Versatile Argument Checks |

cli | 1.1.0 | Helpers for Developing Command Line Interfaces |

clipr | 0.5.0 | Read and Write from the System Clipboard |

coda | 0.19-2 | Output Analysis and Diagnostics for MCMC |

coin | 1.3-0 | Conditional Inference Procedures in a Permutation Test Framework |

colorspace | 1.4-1 | A Toolbox for Manipulating and Assessing Colors and Palettes |

contfrac | 1.1-12 | Continued Fractions |

crayon | 1.3.4 | Colored Terminal Output |

crosstalk | 1.0.0 | Inter-Widget Interactivity for HTML Widgets |

cubature | 2.0.3 | Adaptive Multivariate Integration over Hypercubes |

CVST | 0.2-2 | Fast Cross-Validation via Sequential Testing |

data.table | 1.12.0 | Extension of `data.frame` |

DEoptimR | 1.0-8 | Differential Evolution Optimization in Pure R |

deSolve | 1.21 | Solvers for Initial Value Problems of Differential Equations ('ODE', 'DAE', 'DDE') |

digest | 0.6.18 | Create Compact Hash Digests of R Objects |

dplyr | 0.8.0.1 | A Grammar of Data Manipulation |

DT | 0.5 | A Wrapper of the JavaScript Library 'DataTables' |

ellipsis | 0.1.0 | Tools for Working with ... |

elliptic | 1.4-0 | Weierstrass and Jacobi Elliptic Functions |

emmeans | 1.3.3 | Estimated Marginal Means, aka Least-Squares Means |

estimability | 1.3 | Tools for Assessing Estimability of Linear Predictions |

evaluate | 0.13 | Parsing and Evaluation Tools that Provide More Details than the Default |

fansi | 0.4.0 | ANSI Control Sequence Aware String Functions |

fastDummies | 1.2.0 | Fast Creation of Dummy (Binary) Columns and Rows from Categorical Variables |

fit.models | 0.5-14 | Compare Fitted Models |

forcats | 0.4.0 | Tools for Working with Categorical Variables (Factors) |

foreach | 1.4.4 | Provides Foreach Looping Construct for R |

Formula | 1.2-3 | Extended Model Formulas |

GB2 | 2.1 | Generalized Beta Distribution of the Second Kind: Properties, Likelihood, Estimation |

gbRd | 0.4-11 | Utilities for processing Rd objects and files |

gdata | 2.18.0 | Various R Programming Tools for Data Manipulation |

gee | 4.13-19 | Generalized Estimation Equation Solver |

generics | 0.0.2 | Common S3 Generics not Provided by Base R Methods Related to Model Fitting |

ggeffects | 0.9.0 | Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs |

ggplot2 | 3.1.0 | Create Elegant Data Visualisations Using the Grammar of Graphics |

ggridges | 0.5.1 | Ridgeline Plots in 'ggplot2' |

ggthemes | 4.1.0 | Extra Themes, Scales and Geoms for 'ggplot2' |

glmmTMB | 0.2.3 | Generalized Linear Mixed Models using Template Model Builder |

glue | 1.3.1 | Interpreted String Literals |

gmm | 1.6-2 | Generalized Method of Moments and Generalized Empirical Likelihood |

gmodels | 2.18.1 | Various R Programming Tools for Model Fitting |

gower | 0.2.0 | Gower's Distance |

gridExtra | 2.3 | Miscellaneous Functions for Grid Graphics |

gtable | 0.2.0 | Arrange 'Grobs' in Tables |

gtools | 3.8.1 | Various R Programming Tools |

haven | 2.1.0 | Import and Export 'SPSS', 'Stata' and 'SAS' Files |

highr | 0.7 | Syntax Highlighting for R Source Code |

Hmisc | 4.2-0 | Harrell Miscellaneous |

hms | 0.4.2 | Pretty Time of Day |

htmlTable | 1.13.1 | Advanced Tables for Markdown/HTML |

htmltools | 0.3.6 | Tools for HTML |

htmlwidgets | 1.3 | HTML Widgets for R |

httpuv | 1.5.0 | HTTP and WebSocket Server Library |

huxtable | 4.5.0 | Easily Create and Style Tables for LaTeX, HTML and Other Formats |

hypergeo | 1.2-13 | The Gauss Hypergeometric Function |

IC2 | 1.0-1 | Inequality and Concentration Indices and Curves |

ineq | 0.2-13 | Measuring Inequality, Concentration, and Poverty |

insight | 0.1.2 | Easy Access to Model Information for Various Model Objects |

ipred | 0.9-8 | Improved Predictors |

iterators | 1.0.10 | Provides Iterator Construct for R |

janitor | 1.1.1 | Simple Tools for Examining and Cleaning Dirty Data |

jsonlite | 1.6 | A Robust, High Performance JSON Parser and Generator for R |

kernlab | 0.9-27 | Kernel-Based Machine Learning Lab |

knitr | 1.22 | A General-Purpose Package for Dynamic Report Generation in R |

labeling | 0.3 | Axis Labeling |

laeken | 0.5.0 | Estimation of Indicators on Social Exclusion and Poverty |

later | 0.8.0 | Utilities for Delaying Function Execution |

latticeExtra | 0.6-28 | Extra Graphical Utilities Based on Lattice |

lava | 1.6.5 | Latent Variable Models |

lavaan | 0.6-3 | Latent Variable Analysis |

lazyeval | 0.2.2 | Lazy (Non-Standard) Evaluation |

libcoin | 1.0-4 | Linear Test Statistics for Permutation Inference |

lme4 | 1.1-21 | Linear Mixed-Effects Models using 'Eigen' and S4 |

lmtest | 0.9-36 | Testing Linear Regression Models |

lubridate | 1.7.4 | Make Dealing with Dates a Little Easier |

magrittr | 1.5 | A Forward-Pipe Operator for R |

markdown | 0.9 | 'Markdown' Rendering for R |

Matching | 4.9-5 | Multivariate and Propensity Score Matching with Balance Optimization |

MatchIt | 3.0.2 | Nonparametric Preprocessing for Parametric Causal Inference |

matrixcalc | 1.0-3 | Collection of functions for matrix calculations |

MatrixModels | 0.4-1 | Modelling with Sparse And Dense Matrices |

matrixStats | 0.54.0 | Functions that Apply to Rows and Columns of Matrices (and to Vectors) |

maxLik | 1.3-4 | Maximum Likelihood Estimation and Related Tools |

memoise | 1.1.0 | Memoisation of Functions |

merTools | 0.4.1 | Tools for Analyzing Mixed Effect Regression Models |

mi | 1.0 | Missing Data Imputation and Model Checking |

mime | 0.6 | Map Filenames to MIME Types |

minpack.lm | 1.2-1 | R Interface to the Levenberg-Marquardt Nonlinear Least-Squares Algorithm Found in MINPACK, Plus Support for Bounds |

minqa | 1.2.4 | Derivative-free optimization algorithms by quadratic approximation |

miscTools | 0.6-22 | Miscellaneous Tools and Utilities |

mlogit | 0.4-1 | Multinomial Logit Models |

mnormt | 1.5-5 | The Multivariate Normal and t Distributions |

ModelMetrics | 1.2.2 | Rapid Calculation of Model Metrics |

modelr | 0.1.4 | Modelling Functions that Work with the Pipe |

modeltools | 0.2-22 | Tools and Classes for Statistical Models |

multcomp | 1.4-10 | Simultaneous Inference in General Parametric Models |

munsell | 0.5.0 | Utilities for Using Munsell Colours |

mvtnorm | 1.0-10 | Multivariate Normal and t Distributions |

nleqslv | 3.3.2 | Solve Systems of Nonlinear Equations |

nloptr | 1.2.1 | R Interface to NLopt |

numDeriv | 2016.8-1 | Accurate Numerical Derivatives |

optimx | 2018-7.10 | Expanded Replacement and Extension of the 'optim' Function |

pbivnorm | 0.6.0 | Vectorized Bivariate Normal CDF |

pcaPP | 1.9-73 | Robust PCA by Projection Pursuit |

pillar | 1.3.1 | Coloured Formatting for Columns |

pkgconfig | 2.0.2 | Private Configuration for 'R' Packages |

plogr | 0.2.0 | The 'plog' C++ Logging Library |

plyr | 1.8.4 | Tools for Splitting, Applying and Combining Data |

poLCA | 1.4.1 | Polytomous variable Latent Class Analysis |

prediction | 0.3.6.2 | Tidy, Type-Safe 'prediction()' Methods |

prodlim | 2018.04.18 | Product-Limit Estimation for Censored Event History Analysis |

promises | 1.0.1 | Abstractions for Promise-Based Asynchronous Programming |

psych | 1.8.12 | Procedures for Psychological, Psychometric, and Personality Research |

purrr | 0.3.2 | Functional Programming Tools |

pwr | 1.2-2 | Basic Functions for Power Analysis |

quantreg | 5.38 | Quantile Regression |

R6 | 2.4.0 | Encapsulated Classes with Reference Semantics |

RColorBrewer | 1.1-2 | ColorBrewer Palettes |

Rcpp | 1.0.1 | Seamless R and C++ Integration |

RcppEigen | 0.3.3.5.0 | 'Rcpp' Integration for the 'Eigen' Templated Linear Algebra Library |

RcppRoll | 0.3.0 | Efficient Rolling / Windowed Operations |

Rdpack | 0.10-1 | Update and Manipulate Rd Documentation Objects |

readr | 1.3.1 | Read Rectangular Text Data |

readstata13 | 0.9.2 | Import 'Stata' Data Files |

recipes | 0.1.4 | Preprocessing Tools to Create Design Matrices |

reshape2 | 1.4.3 | Flexibly Reshape Data: A Reboot of the Reshape Package |

rgenoud | 5.8-3.0 | R Version of GENetic Optimization Using Derivatives |

rlang | 0.3.1 | Functions for Base Types and Core R and 'Tidyverse' Features |

robust | 0.4-18 | Port of the S+ Robust Library |

robustbase | 0.93-4 | Basic Robust Statistics |

rrcov | 1.4-7 | Scalable Robust Estimators with High Breakdown Point |

rstudioapi | 0.9.0 | Safely Access the RStudio API |

sandwich | 2.5-0 | Robust Covariance Matrix Estimators |

scales | 1.0.0 | Scale Functions for Visualization |

scatterplot3d | 0.3-41 | 3D Scatter Plot |

sem | 3.1-9 | Structural Equation Models |

sjlabelled | 1.0.17 | Labelled Data Utility Functions |

sjmisc | 2.7.9 | Data and Variable Transformation Functions |

sjPlot | 2.6.2 | Data Visualization for Statistics in Social Science |

sjstats | 0.17.4 | Collection of Convenient Functions for Common Statistical Computations |

snakecase | 0.9.2 | Convert Strings into any Case |

sourcetools | 0.1.7 | Tools for Reading, Tokenizing and Parsing R Code |

SparseM | 1.77 | Sparse Linear Algebra |

SQUAREM | 2017.10-1 | Squared Extrapolation Methods for Accelerating EM-Like Monotone Algorithms |

stargazer | 5.2.2 | Well-Formatted Regression and Summary Statistics Tables |

statmod | 1.4.30 | Statistical Modeling |

stringdist | 0.9.5.1 | Approximate String Matching and String Distance Functions |

stringi | 1.4.3 | Character String Processing Facilities |

stringr | 1.4.0 | Simple, Consistent Wrappers for Common String Operations |

survey | 3.35-1 | Analysis of Complex Survey Samples |

TH.data | 1.0-10 | TH's Data Archive |

tibble | 2.1.1 | Simple Data Frames |

tidyr | 0.8.3 | Easily Tidy Data with 'spread()' and 'gather()' Functions |

tidyselect | 0.2.5 | Select from a Set of Strings |

timeDate | 3043.102 | Rmetrics - Chronological and Calendar Objects |

TMB | 1.7.15 | Template Model Builder: A General Random Effect Tool Inspired by 'ADMB' |

utf8 | 1.1.4 | Unicode Text Processing |

viridis | 0.5.1 | Default Color Maps from 'matplotlib' |

viridisLite | 0.3.0 | Default Color Maps from 'matplotlib' (Lite Version) |

withr | 2.1.2 | Run Code 'With' Temporarily Modified Global State |

xfun | 0.5 | Miscellaneous Functions by 'Yihui Xie' |

xtable | 1.8-3 | Export Tables to LaTeX or HTML |

yaml | 2.2.0 | Methods to Convert R Data to YAML and Back |

zoo | 1.8-4 | S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations) |