Repeated Cross-Sectional Randomized Response Data: Taking Design Change and Self-Protective Responses into Account
Randomized response (RR) is an interview technique that can be used to protect the privacy of respondents if sensitive questions are posed. This paper explains how to measure change in time if a binary RR question is posed at several time points. In cross-sectional research settings, new insights of...
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| Veröffentlicht in: | Methodology 2009, Vol.5 (4), p.145-152 |
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| container_title | Methodology |
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| creator | Frank, L. E van den Hout, A van der Heijden, P. G. M |
| description | Randomized response (RR) is an interview technique that can be used to protect
the privacy of respondents if sensitive questions are posed. This paper explains
how to measure change in time if a binary RR question is posed at several time
points. In cross-sectional research settings, new insights often gradually
emerge. In our setting, a switch to another RR procedure necessitates the
development of a trend model that estimates the effect of the covariate time if
the dependent variable is measured by different RR designs. We also demonstrate
that it is possible to deal with self-protective responses, thus accommodating
our trend model with the latest developments in RR data analysis. |
| doi_str_mv | 10.1027/1614-2241.5.4.145 |
| format | Article |
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the privacy of respondents if sensitive questions are posed. This paper explains
how to measure change in time if a binary RR question is posed at several time
points. In cross-sectional research settings, new insights often gradually
emerge. In our setting, a switch to another RR procedure necessitates the
development of a trend model that estimates the effect of the covariate time if
the dependent variable is measured by different RR designs. We also demonstrate
that it is possible to deal with self-protective responses, thus accommodating
our trend model with the latest developments in RR data analysis.</description><identifier>ISSN: 1614-1881</identifier><identifier>EISSN: 1614-2241</identifier><identifier>DOI: 10.1027/1614-2241.5.4.145</identifier><language>eng</language><publisher>Göttingen: Hogrefe & Huber Publishers</publisher><subject>Biological and medical sciences ; Dependent Variables ; Fundamental and applied biological sciences. Psychology ; Interviewing ; Linear Regression ; Methodology ; Privacy ; Psychology. Psychoanalysis. Psychiatry ; Psychology. Psychophysiology ; Psychometrics ; Psychometrics. Statistics. Methodology ; Response Parameters ; Statistics. Mathematics ; Trends</subject><ispartof>Methodology, 2009, Vol.5 (4), p.145-152</ispartof><rights>2009 Hogrefe & Huber Publishers</rights><rights>2015 INIST-CNRS</rights><rights>2009, Hogrefe & Huber Publishers</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a317t-90011de62555c03953b306690e763fa8c753da65171f63da18781feee864236c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,4024,27923,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23707680$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Frank, L. E</creatorcontrib><creatorcontrib>van den Hout, A</creatorcontrib><creatorcontrib>van der Heijden, P. G. M</creatorcontrib><title>Repeated Cross-Sectional Randomized Response Data: Taking Design Change and Self-Protective Responses into Account</title><title>Methodology</title><description>Randomized response (RR) is an interview technique that can be used to protect
the privacy of respondents if sensitive questions are posed. This paper explains
how to measure change in time if a binary RR question is posed at several time
points. In cross-sectional research settings, new insights often gradually
emerge. In our setting, a switch to another RR procedure necessitates the
development of a trend model that estimates the effect of the covariate time if
the dependent variable is measured by different RR designs. We also demonstrate
that it is possible to deal with self-protective responses, thus accommodating
our trend model with the latest developments in RR data analysis.</description><subject>Biological and medical sciences</subject><subject>Dependent Variables</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Interviewing</subject><subject>Linear Regression</subject><subject>Methodology</subject><subject>Privacy</subject><subject>Psychology. Psychoanalysis. Psychiatry</subject><subject>Psychology. Psychophysiology</subject><subject>Psychometrics</subject><subject>Psychometrics. Statistics. Methodology</subject><subject>Response Parameters</subject><subject>Statistics. Mathematics</subject><subject>Trends</subject><issn>1614-1881</issn><issn>1614-2241</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><recordid>eNptkE1Lw0AQhhdRsFZ_gLeieBESd7JfyVHqJxSEqudl3EwgJU3ibnrQX--GlqLgaYaZ5315Zxg7B54Cz8wNaJBJlklIVSpTkOqATfazw10PeQ7H7CSEFecyTsyEwZJ6woHK2dx3ISSv5Ia6a7GZLbEtu3X9HVdLCn3XBprd4YCn7KjCJtDZrk7Z-8P92_wpWbw8Ps9vFwkKMENScA5Qks6UUo6LQokPwbUuOBktKsydUaJErcBApWMHucmhIqJcy0xoJ6bsYuvb--5zQ2Gwq27jY7Jg4y2KF5oXEYIt5Mb0nirb-3qN_ssCt-Nj7Hi4HZ9glZU2CqPmameMwWFTeWxdHfbCTBhudM4jd73lsEfbhy-HfqhdQ8FtvKd2sGsqf5le_g__oX4AKgd7lg</recordid><startdate>2009</startdate><enddate>2009</enddate><creator>Frank, L. E</creator><creator>van den Hout, A</creator><creator>van der Heijden, P. G. M</creator><general>Hogrefe & Huber Publishers</general><general>Hogrefe</general><general>Hogrefe Publishing</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7RZ</scope><scope>PSYQQ</scope></search><sort><creationdate>2009</creationdate><title>Repeated Cross-Sectional Randomized Response Data</title><author>Frank, L. E ; van den Hout, A ; van der Heijden, P. G. M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a317t-90011de62555c03953b306690e763fa8c753da65171f63da18781feee864236c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Biological and medical sciences</topic><topic>Dependent Variables</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Interviewing</topic><topic>Linear Regression</topic><topic>Methodology</topic><topic>Privacy</topic><topic>Psychology. Psychoanalysis. Psychiatry</topic><topic>Psychology. Psychophysiology</topic><topic>Psychometrics</topic><topic>Psychometrics. Statistics. Methodology</topic><topic>Response Parameters</topic><topic>Statistics. Mathematics</topic><topic>Trends</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Frank, L. E</creatorcontrib><creatorcontrib>van den Hout, A</creatorcontrib><creatorcontrib>van der Heijden, P. G. M</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Access via APA PsycArticles® (ProQuest)</collection><collection>ProQuest One Psychology</collection><jtitle>Methodology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Frank, L. E</au><au>van den Hout, A</au><au>van der Heijden, P. G. M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Repeated Cross-Sectional Randomized Response Data: Taking Design Change and Self-Protective Responses into Account</atitle><jtitle>Methodology</jtitle><date>2009</date><risdate>2009</risdate><volume>5</volume><issue>4</issue><spage>145</spage><epage>152</epage><pages>145-152</pages><issn>1614-1881</issn><eissn>1614-2241</eissn><abstract>Randomized response (RR) is an interview technique that can be used to protect
the privacy of respondents if sensitive questions are posed. This paper explains
how to measure change in time if a binary RR question is posed at several time
points. In cross-sectional research settings, new insights often gradually
emerge. In our setting, a switch to another RR procedure necessitates the
development of a trend model that estimates the effect of the covariate time if
the dependent variable is measured by different RR designs. We also demonstrate
that it is possible to deal with self-protective responses, thus accommodating
our trend model with the latest developments in RR data analysis.</abstract><cop>Göttingen</cop><pub>Hogrefe & Huber Publishers</pub><doi>10.1027/1614-2241.5.4.145</doi><tpages>8</tpages></addata></record> |
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| ispartof | Methodology, 2009, Vol.5 (4), p.145-152 |
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| source | EBSCOhost APA PsycARTICLES; Hogrefe eContent |
| subjects | Biological and medical sciences Dependent Variables Fundamental and applied biological sciences. Psychology Interviewing Linear Regression Methodology Privacy Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Psychometrics Psychometrics. Statistics. Methodology Response Parameters Statistics. Mathematics Trends |
| title | Repeated Cross-Sectional Randomized Response Data: Taking Design Change and Self-Protective Responses into Account |
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