Job Submission

Submit jobs through LISSY web-based interface

Once connected to LISSY through the web-based interface with the userid and password received during the registration process, you can

  • Write and submit statistical requests in R, SAS, SPSS and Stata (Job Session Pane)
  • Track job status and view both job request and resulting listing (Recent Jobs Pane)
  • Manage (view, clean and search) all job requests you ever sent (Job Archive Pane)

Note that, for security reasons, the output of all job requests will be returned to the email registered in LISSY.

In order for LISSY to process user requests properly, a few exceptions to the usual statistical program syntax are required. If you are not familiar with statistical package coding first visit our Get Started with LISSY section.

Job Submission Syntax

Dataset Aliases

A LIS (or LWS) dataset refers to harmonised microdata for one country and one year and consists of two datafiles: one household-level file and one individual-level file including their respective household members. Some LWS datasets include a household-level replicate weights file. Instead of using file names, datafiles are referred to by short aliases, constructed as follows:

  • The concatenation of the 2-digit 3166 ISO country code with the last 2-digits of the dataset reference year
  • A letter used to identify the specific type of dataset within each database
Database Database Type Letter Code
LIS Household File h
Person File p
LWS Household File h
Person File p
Implicate File r
ERFLIS Household File h
Person File p

As an example, Luxembourg 2004 household-level LIS (or LWS) datafile is identified by the same alias lu04h.

Datafile Calling by Statistical Package

In all statistical packages, calling a datafile requires to refer to its complete filename, which generally consists of a path, a name and an extension. In LISSY, we have created specific syntax – by statistical package – to call a dataset file based on its alias. As an example calling Luxembourg 2010 Household file (alias lu10h):

Statistical Package How to call a data file Syntax example
R * Pass the alias as a string to a special function read.LIS ds <- read.LIS('lu10h');
SAS Place the & character before the alias PROC MEANS DATA=&lu10h;
SPSS Use the alias with no prefix get file = lu10h
Stata Place the $ character before the alias use $lu10h

*  This function has some additional parameters for user convenience. In addition, due to LIS security procedures, the syntax for generating output with R in LISSY is slightly changed. click here for detailed information.

Producing graphs by Statistical Package

In LISSY, we have created specific syntax to be used in combination with the syntax of each graph – by statistical package – this syntax allows users to display their graphs on the Web-based Job Submission Interface and download it in PDF or png format. See the below example for producing a simple twoway graph, the part of syntax that should be included in all the graphs syntax are in red :

Statistical Package Syntax example
R library(foreign)
library(readstata13)
data <- read.LIS('lu10p') attach(data)

png(file = “USR_PDF,graphtestR.png”,width=1200,height=1000)
plot(edyrs, pi11)
abline(lm(pi11~edyrs))
title(“Regression of education on wage”)
SAS FILENAME output
“&mypdf/graphtestsas.png”;

GOPTIONS RESET=ALL DEVICE=PNG GSFNAME=output GSFMODE=REPLACE;
PROC GCHART data=&lu10p;
VBAR age / TYPE=percent;
RUN;
SPSS GET FILE = lu10p.           
GRAPH           
                             /BAR(SIMPLE)=relation BY edyrs.           
OUTPUT EXPORT /JPG DOCUMENTFILE=”mypdf\graphtestspss.jpg
Stata use $lu10p, clear
twoway (lfit pi11 edyrs)
graphexportpdf $mypdf/graphteststata

List of LIS and LWS Datasets

LIS supplies a file that includes a list of datasets that can be used through LISSY, this file includes characteristics to identify LIS and LWS online datasets.

The file exists in either .dta or .txt format. See below the syntax to access these files in R, SAS or Stata:

Database File Statistical Package Syntax
LIS / LWS List of datasets R read.dta13(paste(INC_DIR, “datasets.dta”, sep=””),convert.factors=FALSE)
SAS proc import datafile = “&myincl.datasets.txt”
out = datasets
dbms = dlm
replace;
delimiter = ‘,’ ;
run;
Stata use $myincl/datasets.dta

LIS PPPs Deflators

LIS provides a list of LIS PPPs deflators that can be accessed through LISSY.
The list of LIS PPP deflators enables adjusting either income, consumption or wealth variable in a given country in a given year to 2011 or 2017 USD PPPs (files ppp_2017 and ppp_2011). This list is also available online here.

Each file exists in either .dta or .txt format. See below the syntax to access these files in R, SAS or Stata :

Database File Statistical Package Syntax
LIS / LWS List of datasets R read.dta13(paste(INC_DIR, “ppp_2017.dta”, sep=””),convert.factors=FALSE)
SAS proc import datafile = “&myincl.ppp_2017.txt”
out = ppps
dbms = dlm
replace;
delimiter = ‘,’ ;
run;
Stata use $myincl/ppp_2017.dta

Note: The old LIS 2011 PPPs file is still accessible via LISSY

LISSY Coding Best Practices

The LISSY system processes received jobs and returns listings with aggregated results, usually within minutes. However, LISSY’s processing time can vary depending on the total number of submitted jobs at a given time and on the complexity of each job. We recommend to apply the followings to avoid system congestion

  • Send each job only once. If it is not returned, do not send it again.
  • Wait for each job to be returned before submitting your next one.
  • Do not request frequencies on continuous variables or use commands that violate our security measures. Certain program syntax and commands will trigger system security alerts and may interrupt traffic. See our FAQs for tips on avoiding disallowed commands.
  • Try breaking up statistical queries into several smaller jobs because jobs that result in very long output may cause system congestion. If you encounter difficulties repeatedly, please contact User Support.
  • Debug your program before submitting a job to LISSY, especially if you are not familiar with statistical package syntax. Debugging can be done on your home computer by testing your jobs on our downloadable sample files.