http://wiki.stat.ucla.edu/hpmrg/index.php?title=HPMRG:About&feed=atom&action=historyHPMRG:About - Revision history2024-03-28T10:14:33ZRevision history for this page on the wikiMediaWiki 1.15.2http://wiki.stat.ucla.edu/hpmrg/index.php?title=HPMRG:About&diff=359&oldid=prevHandcock: Redirected page to Hard-to-Reach Population Methods Research Group2011-04-28T22:50:59Z<p>Redirected page to <a href="/hpmrg/index.php/Hard-to-Reach_Population_Methods_Research_Group" title="Hard-to-Reach Population Methods Research Group">Hard-to-Reach Population Methods Research Group</a></p>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">The </del>Hard-to-Reach Population Methods Research Group <del class="diffchange diffchange-inline">(HPMRG) focuses on developing statistical methodology to help improve understanding of hard-to-reach or otherwise "hidden" populations.</del></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">#REDIRECT [[</ins>Hard-to-Reach Population Methods Research Group]]</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div> </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">These populations are characterized by the difficulty in survey sampling from them using standard probability methods. Typically, a sampling frame for the target population is not available, and its members are rare or stigmatized in the larger population so that it is prohibitively expensive to contact them through the available frames. Examples of such populations in a behavioral and social setting include injection drug users, men who have sex with men, and female sex workers. Examples in an economic setting include unregulated workers and the self-employed. Hard-to-reach populations in the US and elsewhere are under-served by current sampling methodologies mainly due to the lack of practical alternatives to address these methodological difficulties.</del></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div> </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">The Hard-to-Reach Population Methods Research Group is an collaborative interdisciplinary group of researchers from several universities:</del></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div> </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">'''Dr. Krista J. Gile''' is a Postdoctoral Prize Research Fellow at Nuffield College at the University of Oxford. Her research focuses on developing statistical methodology for social and behavioral science research, particularly related to making inference from partially-observed social network structures. Most of her current work is focused on understanding the strengths and limitations of data sampled with link-tracing designs such as snowball sampling, contact tracing, and respondent-driven sampling. In particular, her dissertation and recent work focus on understanding the implications of assumptions of current respondent-driven sampling (RDS) methodology, and on introducing improved estimation strategies for RDS data. For details see [http://www.math.umass.edu/~gile her web page</del>]<del class="diffchange diffchange-inline">.</del></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div> </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">'''Dr. Mark S. Handcock''' is Professor of Statistics in the Department of Statistics at the University of California – Los Angeles. His research involves methodological development, and is based largely on motivation from questions in the social and epidemiological sciences. He has published extensively on survey sampling, network inference, and network sampling methods. He recently moved to UCLA from the University of Washington. He teaches [http://www.stat.washington.edu/~handcock/567/ ''Statistical Analysis of Networks''] and [http://www.stat.washington.edu/~handcock/529/ ''Sample Survey Techniques'']. For details see [http://www.stat.ucla.edu/~handcock his web page].</del></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div> </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">'''Dr. Lisa G. Johnston''' is an epidemiologist, applied researcher and RDS consultant. Dr. Johnston has six years of experience providing supervision and training on using RDS methods, HIV/STI biological-behavioral surveillance survey planning and implementation, and the RDS Analysis Tool (RDSAT). She has provided RDS technical assistance in over 30 countries and has done extensive consulting for the Center for Disease Control and Prevention (CDC) and many other institutions including Family Health International (FHI), United Nations Development Program, and UNAIDS. She is currently adjunct professor at Tulane University, School of Public Health and Tropical Medicine, and a Senior Analyst at the University of California, San Francisco, Global Health Sciences. For details see [http://www.lisagjohnston.com/ her web page].</del></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div> </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">'''Dr. Cori M. Mar''' is the Director of the Statistics Core at the Center for Studies in Demography and Ecology (CSDE) at the University of Washington. Her duties include providing training in statistical methods, data analysis techniques, and statistical programming. Dr. Mar has taught R in a variety of formats from a 2-3 hour one class introduction to one hour a week through a 10 week course. Dr. Mar has extensive experience as a translator between statisticians and the applied researchers. For details see [http://csde.washington.edu/services/statistics.shtml her web page</del>]<del class="diffchange diffchange-inline">.</del></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div></div></td></tr>
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</table>Handcockhttp://wiki.stat.ucla.edu/hpmrg/index.php?title=HPMRG:About&diff=311&oldid=prevHandcock at 21:30, 28 March 20112011-03-28T21:30:00Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>The Hard-to-Reach Population Methods Research Group is an collaborative interdisciplinary group of researchers from several universities:</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>The Hard-to-Reach Population Methods Research Group is an collaborative interdisciplinary group of researchers from several universities:</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>'''Dr. Krista J. Gile''' is a Postdoctoral Prize Research Fellow at Nuffield College at the University of Oxford. Her research focuses on developing statistical methodology for social and behavioral science research, particularly related to making inference from partially-observed social network structures. Most of her current work is focused on understanding the strengths and limitations of data sampled with link-tracing designs such as snowball sampling, contact tracing, and respondent-driven sampling. In particular, her dissertation and recent work focus on understanding the implications of assumptions of current respondent-driven sampling (RDS) methodology, and on introducing improved estimation strategies for RDS data. For details see [http://www.<del class="diffchange diffchange-inline">nuffield</del>.<del class="diffchange diffchange-inline">ox</del>.<del class="diffchange diffchange-inline">ac.uk/users</del>/<del class="diffchange diffchange-inline">gilek </del>her web page].</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>'''Dr. Krista J. Gile''' is a Postdoctoral Prize Research Fellow at Nuffield College at the University of Oxford. Her research focuses on developing statistical methodology for social and behavioral science research, particularly related to making inference from partially-observed social network structures. Most of her current work is focused on understanding the strengths and limitations of data sampled with link-tracing designs such as snowball sampling, contact tracing, and respondent-driven sampling. In particular, her dissertation and recent work focus on understanding the implications of assumptions of current respondent-driven sampling (RDS) methodology, and on introducing improved estimation strategies for RDS data. For details see [http://www.<ins class="diffchange diffchange-inline">math</ins>.<ins class="diffchange diffchange-inline">umass</ins>.<ins class="diffchange diffchange-inline">edu</ins>/<ins class="diffchange diffchange-inline">~gile </ins>her web page].</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>'''Dr. Mark S. Handcock''' is Professor of Statistics in the Department of Statistics at the University of California – Los Angeles. His research involves methodological development, and is based largely on motivation from questions in the social and epidemiological sciences. He has published extensively on survey sampling, network inference, and network sampling methods. He recently moved to UCLA from the University of Washington. He teaches [http://www.stat.washington.edu/~handcock/567/ ''Statistical Analysis of Networks''] and [http://www.stat.washington.edu/~handcock/529/ ''Sample Survey Techniques'']. For details see [http://www.stat.ucla.edu/~handcock his web page].</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>'''Dr. Mark S. Handcock''' is Professor of Statistics in the Department of Statistics at the University of California – Los Angeles. His research involves methodological development, and is based largely on motivation from questions in the social and epidemiological sciences. He has published extensively on survey sampling, network inference, and network sampling methods. He recently moved to UCLA from the University of Washington. He teaches [http://www.stat.washington.edu/~handcock/567/ ''Statistical Analysis of Networks''] and [http://www.stat.washington.edu/~handcock/529/ ''Sample Survey Techniques'']. For details see [http://www.stat.ucla.edu/~handcock his web page].</div></td></tr>
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</table>Handcockhttp://wiki.stat.ucla.edu/hpmrg/index.php?title=HPMRG:About&diff=310&oldid=prevHandcock at 21:27, 28 March 20112011-03-28T21:27:58Z<p></p>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>The <del class="diffchange diffchange-inline">Hidden </del>Population Methods Research Group (HPMRG) focuses on developing statistical methodology to help improve understanding of hard-to-reach or otherwise "hidden" populations.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>The <ins class="diffchange diffchange-inline">Hard-to-Reach </ins>Population Methods Research Group (HPMRG) focuses on developing statistical methodology to help improve understanding of hard-to-reach or otherwise "hidden" populations.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>These populations are characterized by the difficulty in survey sampling from them using standard probability methods. Typically, a sampling frame for the target population is not available, and its members are rare or stigmatized in the larger population so that it is prohibitively expensive to contact them through the available frames. Examples of such populations in a behavioral and social setting include injection drug users, men who have sex with men, and female sex workers. Examples in an economic setting include unregulated workers and the self-employed. Hard-to-reach populations in the US and elsewhere are under-served by current sampling methodologies mainly due to the lack of practical alternatives to address these methodological difficulties.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>These populations are characterized by the difficulty in survey sampling from them using standard probability methods. Typically, a sampling frame for the target population is not available, and its members are rare or stigmatized in the larger population so that it is prohibitively expensive to contact them through the available frames. Examples of such populations in a behavioral and social setting include injection drug users, men who have sex with men, and female sex workers. Examples in an economic setting include unregulated workers and the self-employed. Hard-to-reach populations in the US and elsewhere are under-served by current sampling methodologies mainly due to the lack of practical alternatives to address these methodological difficulties.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>The <del class="diffchange diffchange-inline">Hidden </del>Population Methods Research Group is an collaborative interdisciplinary group of researchers from several universities:</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>The <ins class="diffchange diffchange-inline">Hard-to-Reach </ins>Population Methods Research Group is an collaborative interdisciplinary group of researchers from several universities:</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>'''Dr. Krista J. Gile''' is a Postdoctoral Prize Research Fellow at Nuffield College at the University of Oxford. Her research focuses on developing statistical methodology for social and behavioral science research, particularly related to making inference from partially-observed social network structures. Most of her current work is focused on understanding the strengths and limitations of data sampled with link-tracing designs such as snowball sampling, contact tracing, and respondent-driven sampling. In particular, her dissertation and recent work focus on understanding the implications of assumptions of current respondent-driven sampling (RDS) methodology, and on introducing improved estimation strategies for RDS data. For details see [http://www.nuffield.ox.ac.uk/users/gilek her web page].</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>'''Dr. Krista J. Gile''' is a Postdoctoral Prize Research Fellow at Nuffield College at the University of Oxford. Her research focuses on developing statistical methodology for social and behavioral science research, particularly related to making inference from partially-observed social network structures. Most of her current work is focused on understanding the strengths and limitations of data sampled with link-tracing designs such as snowball sampling, contact tracing, and respondent-driven sampling. In particular, her dissertation and recent work focus on understanding the implications of assumptions of current respondent-driven sampling (RDS) methodology, and on introducing improved estimation strategies for RDS data. For details see [http://www.nuffield.ox.ac.uk/users/gilek her web page].</div></td></tr>
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</table>Handcockhttp://wiki.stat.ucla.edu/hpmrg/index.php?title=HPMRG:About&diff=102&oldid=prevHandcock at 07:51, 5 June 20102010-06-05T07:51:48Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>The Hidden Population Methods Research Group is an collaborative interdisciplinary group of researchers from several universities:</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>The Hidden Population Methods Research Group is an collaborative interdisciplinary group of researchers from several universities:</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>'''Dr. Krista J. Gile''' is a Postdoctoral Prize Research Fellow at Nuffield College at the University of Oxford. Her research focuses on developing statistical methodology for social and behavioral science research, particularly related to making inference from partially-observed social network structures. Most of her current work is focused on understanding the strengths and limitations of data sampled with link-tracing designs such as snowball sampling, contact tracing, and respondent-driven sampling. In particular, her dissertation and recent work focus on understanding the implications of assumptions of current RDS methodology, and on introducing improved estimation strategies for RDS data. For details see [http://www.nuffield.ox.ac.uk/users/gilek<del class="diffchange diffchange-inline">| </del>her web page].</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>'''Dr. Krista J. Gile''' is a Postdoctoral Prize Research Fellow at Nuffield College at the University of Oxford. Her research focuses on developing statistical methodology for social and behavioral science research, particularly related to making inference from partially-observed social network structures. Most of her current work is focused on understanding the strengths and limitations of data sampled with link-tracing designs such as snowball sampling, contact tracing, and respondent-driven sampling. In particular, her dissertation and recent work focus on understanding the implications of assumptions of current <ins class="diffchange diffchange-inline">respondent-driven sampling (</ins>RDS<ins class="diffchange diffchange-inline">) </ins>methodology, and on introducing improved estimation strategies for RDS data. For details see [http://www.nuffield.ox.ac.uk/users/gilek her web page].</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>'''Dr. Mark S. Handcock''' is Professor of Statistics in the Department of Statistics at the University of California – Los Angeles. His research involves methodological development, and is based largely on motivation from questions in the social and epidemiological sciences. He has published extensively on survey sampling, network inference, and network sampling methods. He recently moved to UCLA from the University of Washington. He teaches [http://www.stat.washington.edu/~handcock/567/<del class="diffchange diffchange-inline">| </del>''Statistical Analysis of Networks''] and [http://www.stat.washington.edu/~handcock/529/<del class="diffchange diffchange-inline">| </del>''Sample Survey Techniques'']. For details see [http://www.stat.ucla.edu/handcock<del class="diffchange diffchange-inline">| </del>his web page].</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>'''Dr. Mark S. Handcock''' is Professor of Statistics in the Department of Statistics at the University of California – Los Angeles. His research involves methodological development, and is based largely on motivation from questions in the social and epidemiological sciences. He has published extensively on survey sampling, network inference, and network sampling methods. He recently moved to UCLA from the University of Washington. He teaches [http://www.stat.washington.edu/~handcock/567/ ''Statistical Analysis of Networks''] and [http://www.stat.washington.edu/~handcock/529/ ''Sample Survey Techniques'']. For details see [http://www.stat.ucla.edu/<ins class="diffchange diffchange-inline">~</ins>handcock his web page].</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>'''Dr. Lisa G. Johnston''' is an epidemiologist, applied researcher and RDS consultant. Dr. Johnston has six years of experience providing supervision and training on using RDS methods, HIV/STI biological-behavioral surveillance survey planning and implementation, and the RDS Analysis Tool (RDSAT). She has provided RDS technical assistance in over 30 countries and has done extensive consulting for the Center for Disease Control and Prevention (CDC) and many other institutions including Family Health International (FHI), United Nations Development Program, and UNAIDS. She is currently adjunct professor at Tulane University, School of Public Health and Tropical Medicine, and a Senior Analyst at the University of California, San Francisco, Global Health Sciences. For details see [http://www.lisagjohnston.com/<del class="diffchange diffchange-inline">| </del>her web page].</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>'''Dr. Lisa G. Johnston''' is an epidemiologist, applied researcher and RDS consultant. Dr. Johnston has six years of experience providing supervision and training on using RDS methods, HIV/STI biological-behavioral surveillance survey planning and implementation, and the RDS Analysis Tool (RDSAT). She has provided RDS technical assistance in over 30 countries and has done extensive consulting for the Center for Disease Control and Prevention (CDC) and many other institutions including Family Health International (FHI), United Nations Development Program, and UNAIDS. She is currently adjunct professor at Tulane University, School of Public Health and Tropical Medicine, and a Senior Analyst at the University of California, San Francisco, Global Health Sciences. For details see [http://www.lisagjohnston.com/ her web page].</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>'''Dr. Cori Mar''' is the Director of the Statistics Core at the Center for Studies in Demography and Ecology (CSDE) at the University of Washington. Her duties include providing training in statistical methods, data analysis techniques, and statistical programming. Dr. Mar has taught R in a variety of formats from a 2-3 hour one class introduction to one hour a week through a 10 week course. Dr. Mar has extensive experience as a translator between statisticians and the applied researchers. For details see [http://csde.washington.edu/services/statistics.shtml<del class="diffchange diffchange-inline">| </del>her web page].</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>'''Dr. Cori <ins class="diffchange diffchange-inline">M. </ins>Mar''' is the Director of the Statistics Core at the Center for Studies in Demography and Ecology (CSDE) at the University of Washington. Her duties include providing training in statistical methods, data analysis techniques, and statistical programming. Dr. Mar has taught R in a variety of formats from a 2-3 hour one class introduction to one hour a week through a 10 week course. Dr. Mar has extensive experience as a translator between statisticians and the applied researchers. For details see [http://csde.washington.edu/services/statistics.shtml her web page].</div></td></tr>
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</table>Handcockhttp://wiki.stat.ucla.edu/hpmrg/index.php?title=HPMRG:About&diff=93&oldid=prevHandcock at 07:44, 5 June 20102010-06-05T07:44:34Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>'''Dr. Krista J. Gile''' is a Postdoctoral Prize Research Fellow at Nuffield College at the University of Oxford. Her research focuses on developing statistical methodology for social and behavioral science research, particularly related to making inference from partially-observed social network structures. Most of her current work is focused on understanding the strengths and limitations of data sampled with link-tracing designs such as snowball sampling, contact tracing, and respondent-driven sampling. In particular, her dissertation and recent work focus on understanding the implications of assumptions of current RDS methodology, and on introducing improved estimation strategies for RDS data. For details see [http://www.nuffield.ox.ac.uk/users/gilek| her web page].</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>'''Dr. Krista J. Gile''' is a Postdoctoral Prize Research Fellow at Nuffield College at the University of Oxford. Her research focuses on developing statistical methodology for social and behavioral science research, particularly related to making inference from partially-observed social network structures. Most of her current work is focused on understanding the strengths and limitations of data sampled with link-tracing designs such as snowball sampling, contact tracing, and respondent-driven sampling. In particular, her dissertation and recent work focus on understanding the implications of assumptions of current RDS methodology, and on introducing improved estimation strategies for RDS data. For details see [http://www.nuffield.ox.ac.uk/users/gilek| her web page].</div></td></tr>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>'''Dr. Mark S. Handcock''' is Professor of Statistics in the Department of Statistics at the University of California – Los Angeles. His research involves methodological development, and is based largely on motivation from questions in the social and epidemiological sciences. He has published extensively on survey sampling, network inference, and network sampling methods. He recently moved <del class="diffchange diffchange-inline">form </del>the University of Washington. He teaches [http://www.stat.washington.edu/~handcock/567/| ''<del class="diffchange diffchange-inline">Social </del>Analysis of Networks''] and [http://www.stat.washington.edu/~handcock/529/| ''Sample Survey Techniques'']. For details see [http://www.stat.ucla.edu/handcock| his web page].</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>'''Dr. Mark S. Handcock''' is Professor of Statistics in the Department of Statistics at the University of California – Los Angeles. His research involves methodological development, and is based largely on motivation from questions in the social and epidemiological sciences. He has published extensively on survey sampling, network inference, and network sampling methods. He recently moved <ins class="diffchange diffchange-inline">to UCLA from </ins>the University of Washington. He teaches [http://www.stat.washington.edu/~handcock/567/| ''<ins class="diffchange diffchange-inline">Statistical </ins>Analysis of Networks''] and [http://www.stat.washington.edu/~handcock/529/| ''Sample Survey Techniques'']. For details see [http://www.stat.ucla.edu/handcock| his web page].</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>'''Dr. Lisa G. Johnston''' is an epidemiologist, applied researcher and RDS consultant. Dr. Johnston has six years of experience providing supervision and training on using RDS methods, HIV/STI biological-behavioral surveillance survey planning and implementation, and the RDS Analysis Tool (RDSAT). She has provided RDS technical assistance in over 30 countries and has done extensive consulting for the Center for Disease Control and Prevention (CDC) and many other institutions including Family Health International (FHI), United Nations Development Program, and UNAIDS. She is currently adjunct professor at Tulane University, School of Public Health and Tropical Medicine, and a Senior Analyst at the University of California, San Francisco, Global Health Sciences. For details see [http://www.lisagjohnston.com/| her web page].</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>'''Dr. Lisa G. Johnston''' is an epidemiologist, applied researcher and RDS consultant. Dr. Johnston has six years of experience providing supervision and training on using RDS methods, HIV/STI biological-behavioral surveillance survey planning and implementation, and the RDS Analysis Tool (RDSAT). She has provided RDS technical assistance in over 30 countries and has done extensive consulting for the Center for Disease Control and Prevention (CDC) and many other institutions including Family Health International (FHI), United Nations Development Program, and UNAIDS. She is currently adjunct professor at Tulane University, School of Public Health and Tropical Medicine, and a Senior Analyst at the University of California, San Francisco, Global Health Sciences. For details see [http://www.lisagjohnston.com/| her web page].</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>'''Dr. Cori Mar''' is the Director of the Statistics Core at the Center for Studies in Demography and Ecology (CSDE) at the University of Washington. Her duties include providing training in statistical methods, data analysis techniques, and statistical programming. Dr. Mar has taught R in a variety of formats from a 2-3 hour one class introduction to one hour a week through a 10 week course. Dr. Mar has extensive experience as a translator between statisticians and the applied researchers. For details see [http://csde.washington.edu/services/statistics.shtml| her web page].</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>'''Dr. Cori Mar''' is the Director of the Statistics Core at the Center for Studies in Demography and Ecology (CSDE) at the University of Washington. Her duties include providing training in statistical methods, data analysis techniques, and statistical programming. Dr. Mar has taught R in a variety of formats from a 2-3 hour one class introduction to one hour a week through a 10 week course. Dr. Mar has extensive experience as a translator between statisticians and the applied researchers. For details see [http://csde.washington.edu/services/statistics.shtml| her web page].</div></td></tr>
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</table>Handcockhttp://wiki.stat.ucla.edu/hpmrg/index.php?title=HPMRG:About&diff=89&oldid=prevHandcock: Created page with 'The Hidden Population Methods Research Group (HPMRG) focuses on developing statistical methodology to help improve understanding of hard-to-reach or otherwise "hidden" population…'2010-06-05T07:35:43Z<p>Created page with 'The Hidden Population Methods Research Group (HPMRG) focuses on developing statistical methodology to help improve understanding of hard-to-reach or otherwise "hidden" population…'</p>
<p><b>New page</b></p><div>The Hidden Population Methods Research Group (HPMRG) focuses on developing statistical methodology to help improve understanding of hard-to-reach or otherwise "hidden" populations.<br />
<br />
These populations are characterized by the difficulty in survey sampling from them using standard probability methods. Typically, a sampling frame for the target population is not available, and its members are rare or stigmatized in the larger population so that it is prohibitively expensive to contact them through the available frames. Examples of such populations in a behavioral and social setting include injection drug users, men who have sex with men, and female sex workers. Examples in an economic setting include unregulated workers and the self-employed. Hard-to-reach populations in the US and elsewhere are under-served by current sampling methodologies mainly due to the lack of practical alternatives to address these methodological difficulties.<br />
<br />
The Hidden Population Methods Research Group is an collaborative interdisciplinary group of researchers from several universities:<br />
<br />
'''Dr. Krista J. Gile''' is a Postdoctoral Prize Research Fellow at Nuffield College at the University of Oxford. Her research focuses on developing statistical methodology for social and behavioral science research, particularly related to making inference from partially-observed social network structures. Most of her current work is focused on understanding the strengths and limitations of data sampled with link-tracing designs such as snowball sampling, contact tracing, and respondent-driven sampling. In particular, her dissertation and recent work focus on understanding the implications of assumptions of current RDS methodology, and on introducing improved estimation strategies for RDS data. For details see [http://www.nuffield.ox.ac.uk/users/gilek| her web page].<br />
<br />
'''Dr. Mark S. Handcock''' is Professor of Statistics in the Department of Statistics at the University of California – Los Angeles. His research involves methodological development, and is based largely on motivation from questions in the social and epidemiological sciences. He has published extensively on survey sampling, network inference, and network sampling methods. He recently moved form the University of Washington. He teaches [http://www.stat.washington.edu/~handcock/567/| ''Social Analysis of Networks''] and [http://www.stat.washington.edu/~handcock/529/| ''Sample Survey Techniques'']. For details see [http://www.stat.ucla.edu/handcock| his web page].<br />
<br />
'''Dr. Lisa G. Johnston''' is an epidemiologist, applied researcher and RDS consultant. Dr. Johnston has six years of experience providing supervision and training on using RDS methods, HIV/STI biological-behavioral surveillance survey planning and implementation, and the RDS Analysis Tool (RDSAT). She has provided RDS technical assistance in over 30 countries and has done extensive consulting for the Center for Disease Control and Prevention (CDC) and many other institutions including Family Health International (FHI), United Nations Development Program, and UNAIDS. She is currently adjunct professor at Tulane University, School of Public Health and Tropical Medicine, and a Senior Analyst at the University of California, San Francisco, Global Health Sciences. For details see [http://www.lisagjohnston.com/| her web page].<br />
<br />
'''Dr. Cori Mar''' is the Director of the Statistics Core at the Center for Studies in Demography and Ecology (CSDE) at the University of Washington. Her duties include providing training in statistical methods, data analysis techniques, and statistical programming. Dr. Mar has taught R in a variety of formats from a 2-3 hour one class introduction to one hour a week through a 10 week course. Dr. Mar has extensive experience as a translator between statisticians and the applied researchers. For details see [http://csde.washington.edu/services/statistics.shtml| her web page].</div>Handcock