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<page pageid="19" ns="0" title="UCSF 2010 Workshop">
<revisions>
<rev xml:space="preserve">=== Workshop on Respondent-driven Sampling Analyst Software ===
JUNE 15 AND 16, 2010
'''Venue''': University of California, San Francisco. 50 Beale Street, Suite 1200 (12th Floor)
'''Sponsor''': Centers for Disease Control and Prevention Global AIDS Program, Surveillance Branch
==Description==
RDS is a relatively new methodology used worldwide to gather HIV prevalence and risk factors data from hard to reach populations. In this workshop, the Hard-to-Reach Population Methods Research Group (HPMRG) is pleased to introduce a new comprehensive, user friendly and open-source software package for the analysis of RDS Data. The new software, RDS Analyst (RDS-A), includes a user friendly point-and-click graphical user interface allowing for the computation of new and existing estimators and standard errors, visualization of recruitment chains, and diagnostic analysis. It allows for the analysis of multiple variables at once, and the saving and re-use of syntax. For more technical users, the package may also be accessed through a command line interface to the open-source R programming language (http://www.r-project.org/).
The purpose of this 2-day workshop is to introduce RDS-A to researchers already experienced in RDS methodology and statistics. Participants will receive training on the RDS-A state-of-the-art analysis and graphic functions and will be asked to provide feedback in the interest of improving the software prior to more widespread distribution among users of RDS.
This workshop is designed as an introduction to the analysis of RDS data using RDS-A.
It will cover the full RDS-A suite of functions. This begins with data entry and loading data, coding missing data, and re-coding variables. It then treats descriptive and diagnostic methods including visualization methods, followed by existing and new tools for estimation, testing models, confidence intervals and sensitivity analysis. The workshop concludes with an introduction to the re-usable syntax and R command line capabilities of the software.
Workshop participants currently working with RDS data will be encouraged to bring these data, and evaluate them using RDS-A.
The workshop will be open to researchers in epidemiology, social and behavioral sciences with experience using RDS methodology, theory and statistics. You will need to bring a lap top.
The workshop is free, however all travel and other expenses are covered by the participant. We will be forward an agenda and any other pertinent information once you register.
== Outline ==
[http://hpmrg.org/files/rdsaoutline.pdf Outline as PDF]
== Presentations ==
* [http://hpmrg.org/files/RDSAIntroduction.pdf Introduction]
* [http://hpmrg.org/files/SamplingFundamentalsPresentation.pdf Sampling: A Brief Review], including the [http://hpmrg.org/files/FiguresforSamplingFundamentals.pdf figures].
== RDS Analyst Software ==
[[RDS_Analyst_Manual RDS Analyst manual]], including installation instructions.
The data is at:
C:\Program Files\RDS Analyst\R-2.11.1\library\RDSdevelopment\extdata
== Papers ==
* [http://hpmrg.org/files/gilehandcockSM2010.pdf ''Respondent-Driven Sampling: An Assessment of Current Methodology''] by Krista J. Gile and Mark S. Handcock. To appear in ''Sociological Methodology'', 2010.
== Forum ==
[http://lists.stat.ucla.edu/mailman/listinfo/rdsanalyst_help/ Subscribe to the list]
= Notes taken during the day =
==Sampling: A Review ==
=== Sampling M&Ms ===
* Screen of the table: The goal is to determine the proportion of red in each bag?
* Kitchen side of the table: The goal is to determine the proportion of orange in each bag?
The four bags have: 10%, 20%, 25%, 30%
Four bags:
{|
| || Screen|| Kitchen ||
-
|A = || || E ||
-
|C = || || ||
-
|B = || || ||
-
|H = || || ||
|}
Repeated sampling without replacement. Sample
Screen: 0%, 75%, 0%, 25%
Kitchen: 0%, 75%, 0%, 25%</rev>
</revisions>
</page>
<page pageid="24" ns="0" title="UNAIDS Reference Group Consultation">
<revisions>
<rev xml:space="preserve">=== UNAIDS Reference Group Consultation on Population Size Estimation Based on Respondent-driven Sampling ===
'''Dates''': June 9 - 10, 2014
'''Venue''': University of Massachusetts –Amherst, hosted by the
Statistics Department and Krista Gile
'''Who''': The consultation is called by the UNAIDS Reference Group on
Estimates, Modelling and Projections. We are inviting a diverse group of
field implementers, end data users, and statisticians/mathematicians.
'''Goal''': Obtain methods that may yield valid population size estimates
using data from chain referral sampling. Current methods are largely
considered “good enough” at best. We are looking for additions to the tool
box, preferably better ones.
'''Key objectives''':
* Determine whether the "sequential sampling for population size estimation" (SS-PSE) developed by Handcock-Gile-Mar method yields reasonable size estimates in comparison with existing methods with appropriate attention to assumptions and potential biases.
* Comparison and use of SS-PSE with methods that use additional data sources and collection (capture-recapture, multiplier, mapping).
* Discuss how the above method and other social network-based approaches may provide size estimations of populations that otherwise remain hidden from routine census efforts.
==Background Issues==
The epidemiologic and programmatic need to obtain reasonably accurate size estimates of key populations remains strong in the 3rd decade of the HIV epidemic and response. UNAIDS recently supported elucidation of the Network Scale-Up Method which is not yet widely implemented for a variety of reasons. Currently, the Global Fund, UNAIDS and others are working with MEASURE and University of Manitoba to develop a prototype protocol for programmatic mapping and size estimation. New work by Handcock and Gile develops a size estimator based on social network statistics that estimate the size of a network from incomplete network data. (See [http://arxiv.org/abs/1209.6241 here] for a manuscript). The estimator can be used in a very straightforward manner by nearly anyone who has implemented a respondent driven sampling survey.
Their methodology is implemented in the new [http://wiki.stat.ucla.edu/hpmrg/index.php/RDS_Analyst_Install <u>RDS Analyst</u>] tool developed by Handcock, Fellows and Gile. The field results of this estimator have been analysed by Johnston and others, in comparison with multipliers and capture-recapture results from the same surveys. The estimator should be reviewed independently by the estimates, Projections and Modelling Reference Group, to get a sense of its validity and how it might be used by surveillance teams globally.
==Preliminary Agenda==
The preliminary agenda is [http://hpmrg.org/UNAIDS_Reference_Group_Consultation/RDSSizeAgenda.pdf here]
== Primary Presentations on SS-PSE ==
These are the presentation by Mark S. Handcock, Krista J. Gile and Corinne M. Mar describing the SS-PSE approach:
* [http://hpmrg.org/UNAIDS_Reference_Group_Consultation/UNAIDSUMass14Motivation.pdf Motivations and Objectives of the SS-Size method]
* [http://hpmrg.org/UNAIDS_Reference_Group_Consultation/UNAIDSUMass14Overview.pdf Overview of the SS-Size methodology]
* [http://hpmrg.org/UNAIDS_Reference_Group_Consultation/UNAIDSUMass14Skepticism.pdf Skepticism, Sensitivity and Policy Relevance]
== Software Used in the Presentations ==
===== R package for SS-PSE =====
* The software package <tt>size</tt> package for <tt>R</tt> by Handcock and Gile is available by emailing [mailto:handcock@ucla.edu handcock@ucla.edu]. This is not-publically-released source code, and is made available for the purposes of evaluation and verification.
* The authors of the <tt>size</tt> package believe that it is essential that software for statistical methods be made available with published papers. This is for a number of reasons. Primarily, most modern statistical methods are sufficiently complex to not be fully specified in a research paper. The software then is a primary means to complete the specification of the methodology to the level where it can be used in practice. Hence the software enables the methodology to be assessed, understood, improved and expanded in ways important for scientific progress. In particular, the important goal of reproducibility of research is very difficult to reach without publicly available software. This is the basis we provide it here.
* The software will be publicly announced, following final peer review of the methodology and possible revision. As a condition of using this version, do not redistribute it. It is important that users will see the final version rather than a possibly inconsistent one.
* To install the <tt>size</tt> package directly in binary please use <code>install.packages("size",repos="http://www.stat.ucla.edu/~handcock")</code>
* The <tt>size</tt> package required the <tt>locfit</tt> package (which can be installed via <code>install.packages("locfit")</code>).
<!-- [http://www.hpmrg.org/src/size_0.2.tar.gz ''size'' package for ''R'' by Handcock and Gile (source code); Not for redistribution] -->
* Please make sure that you are running the latest R version (3.1.0). To check which version of R you are using type in R: <code>R.version.string</code>.
* Introduction to the <tt>size</tt> package:
** The primary function to call is "posteriorsize". To get information on it try: <code>> help(posteriorsize)</code><br>
** There are three example code files below. Each fits a simulated RDS degree sequence from a known (simulated) population. <!-- To download them, right click and use the "Save link as" option. -->
*** [http://www.hpmrg.org/software/exampleposteriorsize.simple.R exampleposteriorsize.simple.R]: Tries on a simulated network
*** [http://www.hpmrg.org/software/testnets1000.52.RData testnets1000.52.RData] simulated network with known network size and statistical properties
*** [http://www.hpmrg.org/software/exampleposteriorsize.fauxmadrona.R exampleposteriorsize.fauxmadrona.R] Uses the "fauxmadrona" population
*** [http://www.hpmrg.org/software/exampleposteriorsize.fauxmadrona.flat.R exampleposteriorsize.fauxmadrona.flat.R] Same as above, with a flat prior
**The "fauxmadrona" network is in the [http://cran.r-project.org/web/packages/RDS RDS] package. It has known population size (N=1000) and complex structure. For details see, <code>help(fauxmadrona)</code>.
===== User-friendly software for the analysis of RDS data, including SS-PSE =====
<u>RDS Analyst</u> ('''RDS-A''') is a software package for the analysis of
Respondent-driven sampling (RDS) data that implements recent advances in
statistical methods.
<u>RDS Analyst</u> has an easy-to-use graphical user interface to the powerful and sophisticated capabilities of the computer package [http://r-project.org R]. <u>RDS Analyst</u> has been developed to provide a comprehensive framework for working with RDS data, including tools for sample and population estimations, testing, confidence intervals and sensitivity analysis.
Example capabilities are an easy format for entering data, the visualization of recruitment chains, regression modeling, and missing data.
The interface of <u>RDS Analyst</u> is similar to [http://www.spss.com/ SPSS]. <u>RDS Analyst</u> is
also a free, easy to use, alternative to proprietary data analysis software
such as [http://www.spss.com/ SPSS], [http://www.stata.com/ STATA],
[http://www.sas.com/ SAS]/[http://www.jmp.com/ JMP], and
[http://www.minitab.com/ Minitab]. It has a menu system to do common data
manipulation and analysis tasks, and an Excel-like spreadsheet in which to view
and edit data.
For the manual and download information, go to the [http://hpmrg.org/RDS_Analyst_Manual manual]. More information on installing <u>RDS Analyst</u> can be found [http://wiki.stat.ucla.edu/hpmrg/index.php/RDS_Analyst_Install here].
A video illustrating a very simple use of the population size estimation routines is [http://hpmrg.org/software/RDSAnalystPopulationSizeIllustration.mov here]. The use of the routines to estimate population size in practice requires the specification of other information, as will be described in the meeting.
==== R package for network scale-up method ====
* The software package <tt>networkreporting</tt> package for population size estimation using network scale-up is on CRAN. It is written by Denis Feehan and Matt Salganik.
* To install it from within R, use <code>install.packages("networkreporting")</code>
* This is an alpha release that is meant for people who are already comfortable with R, but will be improved over time.
* The most recent version of the source code is on github: https://github.com/dfeehan/networkreporting.
== Background Papers ==
=== Some statistical background on RDS ===
* [http://arxiv.org/abs/0904.1855 ''Respondent-Driven Sampling: An Assessment of Current Methodology''] by Krista J. Gile and Mark S. Handcock. Pre-print of ''Sociological Methodology'', 40, p 285-327, 2010.
* [http://arxiv.org/abs/1108.0298 ''Network Model-Assisted Inference from Respondent-Driven Sampling Data''] by Krista J. Gile and Mark S. Handcock. arXiv.org, 2011.
=== SS-PSE ===
* [http://hpmrg.org/software/handcockgilemarBiometrics2014.pdf ''Estimating the Size of Populations at High Risk for HIV using Respondent-Driven Sampling Data''] by Mark S. Handcock, Krista J. Gile and Corinne M. Mar. Accepted to ''Biometrics'', 2014.
* [http://arxiv.org/abs/1209.6241 ''Estimating Hidden Population Size using Respondent-Driven Sampling Data''] by Mark S. Handcock, Krista J. Gile and Corinne M. Mar. arXiv.org, 2012.
=== Network Scaleup-type Methods ===
* [http://arxiv.org/abs/1404.4009 ''Estimating the Size of Hidden Populations Using the Generalized Network Scale-Up Estimator''] by Dennis M. Feehan and Matthew J. Salganik. arXiv.org, 2014.
* [http://arxiv.org/abs/1306.0657 ''Estimating Population Size Using the Network Scale Up Method'] by Rachael Maltiel, Adrian E. Raftery, Tyler H. McCormick. arXiv.org, 2013.
=== Time-to-Recruitment Methods ===
* [http://arxiv.org/abs/1406.0721 ''A recruitment model and population size estimation for respondent-driven sampling''] by Forrest W. Crawford. arXiv.org, 2014.
* [http://arxiv.org/abs/1304.3505 ''Modeling and Analysing Respondent Driven Sampling as a Counting Process''] by Yakir Berchenko, Jonathan Rosenblatt, Simon D.W. Frost. arXiv.org, 2013.
== Announcements and Discussion Forum ==
[[RDS Analyst Users Group | Support mailing list for RDA Analyst]]
== Notes taken during the workshop ==</rev>
</revisions>
</page>
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