Estimating Country-Level Terrorism Trends Using Group-Based Trajectory Analyses: Latent Class Growth Analysis and General Mixture Modeling
Recent criminological research has used latent class growth analysis (LCGA), a form of group-based trajectory analysis, to identify distinct terrorism trends and areas of high terrorism activity at the country-level. The current study contributes to the literature by assessing the robustness of rece...
Gespeichert in:
| Veröffentlicht in: | Journal of quantitative criminology 2012-03, Vol.28 (1), p.103-139 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 139 |
|---|---|
| container_issue | 1 |
| container_start_page | 103 |
| container_title | Journal of quantitative criminology |
| container_volume | 28 |
| creator | Morris, Nancy A. Slocum, Lee Ann |
| description | Recent criminological research has used latent class growth analysis (LCGA), a form of group-based trajectory analysis, to identify distinct terrorism trends and areas of high terrorism activity at the country-level. The current study contributes to the literature by assessing the robustness of recent findings generated by one type of group-based analysis, LCGA, to changes in measurement and statistical methodology. Using data from the Global Terrorism Database (GTD), we consider the challenges and advantages of applying group-based analysis to macro-level terrorism data. We summarize and classify country-level patterns of domestic and transnational terrorism using two types of group-based analyses, LCGA and an alternative yet similar modeling approach, general mixture modeling (GMM). We evaluate the results from each approach using both substantive and empirical criteria, highlighting the similarities and differences provided by both techniques. We conclude that both group-based models have utility for terrorism research, yet for the purposes of identifying hot spots of terrorist activity, LCGA results provide greater policy utility. |
| doi_str_mv | 10.1007/s10940-011-9158-2 |
| format | Article |
| fullrecord | <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_1030904972</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>43551924</jstor_id><sourcerecordid>43551924</sourcerecordid><originalsourceid>FETCH-LOGICAL-c370t-a95c4bbe0f125847af3159bf6376d10177400a70bf9a42993b8dcf8fed82db3a3</originalsourceid><addsrcrecordid>eNp9kU9v1DAQxSMEEkvpB-CAZHHiYhj_q21uZVW2lbbqZXuOnGRSssomi8eB7lfgU9dRKpA4cJrD_N4bzXtF8U7AJwFgP5MAr4GDENwL47h8UayEsYpb6_3LYgVWO66NcK-LN0R7APDOyVXx-4pSdwipGx7YepyGFE98iz-xZzuMcYwdHdgu4tAQu6cZ2sRxOvKvgbDJi7DHOo3xxC6H0J8I6QvbhoRDYus-EM30r_T9edsRC0PDNjhgDD277R7TFJHdjg322fpt8aoNPeH58zwr7r9d7dbXfHu3uVlfbnmtLCQevKl1VSG0QhqnbWiVML5qL5S9aAQIazVAsFC1PmjpvapcU7euxcbJplJBnRUfF99jHH9MSKk8dFRj34cBx4lKAQo8aG9lRj_8g-7HKeZnqPQyx-uMUBkSC1THkShiWx5jjjSeslM5l1Mu5ZS5nHIup5yN5aKhzA4PGP8a_0_0fhHtKWf-54pWxggvtXoCnQadEA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>921578513</pqid></control><display><type>article</type><title>Estimating Country-Level Terrorism Trends Using Group-Based Trajectory Analyses: Latent Class Growth Analysis and General Mixture Modeling</title><source>Applied Social Sciences Index & Abstracts (ASSIA)</source><source>Jstor Complete Legacy</source><source>SpringerLink Journals</source><source>HeinOnline Law Journal Library</source><source>Sociological Abstracts</source><creator>Morris, Nancy A. ; Slocum, Lee Ann</creator><creatorcontrib>Morris, Nancy A. ; Slocum, Lee Ann</creatorcontrib><description>Recent criminological research has used latent class growth analysis (LCGA), a form of group-based trajectory analysis, to identify distinct terrorism trends and areas of high terrorism activity at the country-level. The current study contributes to the literature by assessing the robustness of recent findings generated by one type of group-based analysis, LCGA, to changes in measurement and statistical methodology. Using data from the Global Terrorism Database (GTD), we consider the challenges and advantages of applying group-based analysis to macro-level terrorism data. We summarize and classify country-level patterns of domestic and transnational terrorism using two types of group-based analyses, LCGA and an alternative yet similar modeling approach, general mixture modeling (GMM). We evaluate the results from each approach using both substantive and empirical criteria, highlighting the similarities and differences provided by both techniques. We conclude that both group-based models have utility for terrorism research, yet for the purposes of identifying hot spots of terrorist activity, LCGA results provide greater policy utility.</description><identifier>ISSN: 0748-4518</identifier><identifier>EISSN: 1573-7799</identifier><identifier>DOI: 10.1007/s10940-011-9158-2</identifier><identifier>CODEN: JQCRE6</identifier><language>eng</language><publisher>Boston: Springer Science+Business Media</publisher><subject>Analytical estimating ; Countries ; Criminology ; Criminology and Criminal Justice ; Law and Criminology ; Measurement ; Methodology ; Methodology of the Social Sciences ; Mixtures ; Modeling ; Original Paper ; Parametric models ; Research methods ; Robustness ; Sociology ; Statistical discrepancies ; Statistics ; Terrorism ; Trajectories ; Violent crimes</subject><ispartof>Journal of quantitative criminology, 2012-03, Vol.28 (1), p.103-139</ispartof><rights>Springer Science+Business Media, LLC 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c370t-a95c4bbe0f125847af3159bf6376d10177400a70bf9a42993b8dcf8fed82db3a3</citedby><cites>FETCH-LOGICAL-c370t-a95c4bbe0f125847af3159bf6376d10177400a70bf9a42993b8dcf8fed82db3a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/43551924$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/43551924$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,12825,27321,27901,27902,30976,30977,33751,41464,42533,51294,57992,58225</link.rule.ids></links><search><creatorcontrib>Morris, Nancy A.</creatorcontrib><creatorcontrib>Slocum, Lee Ann</creatorcontrib><title>Estimating Country-Level Terrorism Trends Using Group-Based Trajectory Analyses: Latent Class Growth Analysis and General Mixture Modeling</title><title>Journal of quantitative criminology</title><addtitle>J Quant Criminol</addtitle><description>Recent criminological research has used latent class growth analysis (LCGA), a form of group-based trajectory analysis, to identify distinct terrorism trends and areas of high terrorism activity at the country-level. The current study contributes to the literature by assessing the robustness of recent findings generated by one type of group-based analysis, LCGA, to changes in measurement and statistical methodology. Using data from the Global Terrorism Database (GTD), we consider the challenges and advantages of applying group-based analysis to macro-level terrorism data. We summarize and classify country-level patterns of domestic and transnational terrorism using two types of group-based analyses, LCGA and an alternative yet similar modeling approach, general mixture modeling (GMM). We evaluate the results from each approach using both substantive and empirical criteria, highlighting the similarities and differences provided by both techniques. We conclude that both group-based models have utility for terrorism research, yet for the purposes of identifying hot spots of terrorist activity, LCGA results provide greater policy utility.</description><subject>Analytical estimating</subject><subject>Countries</subject><subject>Criminology</subject><subject>Criminology and Criminal Justice</subject><subject>Law and Criminology</subject><subject>Measurement</subject><subject>Methodology</subject><subject>Methodology of the Social Sciences</subject><subject>Mixtures</subject><subject>Modeling</subject><subject>Original Paper</subject><subject>Parametric models</subject><subject>Research methods</subject><subject>Robustness</subject><subject>Sociology</subject><subject>Statistical discrepancies</subject><subject>Statistics</subject><subject>Terrorism</subject><subject>Trajectories</subject><subject>Violent crimes</subject><issn>0748-4518</issn><issn>1573-7799</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>7QJ</sourceid><sourceid>BENPR</sourceid><sourceid>BHHNA</sourceid><recordid>eNp9kU9v1DAQxSMEEkvpB-CAZHHiYhj_q21uZVW2lbbqZXuOnGRSssomi8eB7lfgU9dRKpA4cJrD_N4bzXtF8U7AJwFgP5MAr4GDENwL47h8UayEsYpb6_3LYgVWO66NcK-LN0R7APDOyVXx-4pSdwipGx7YepyGFE98iz-xZzuMcYwdHdgu4tAQu6cZ2sRxOvKvgbDJi7DHOo3xxC6H0J8I6QvbhoRDYus-EM30r_T9edsRC0PDNjhgDD277R7TFJHdjg322fpt8aoNPeH58zwr7r9d7dbXfHu3uVlfbnmtLCQevKl1VSG0QhqnbWiVML5qL5S9aAQIazVAsFC1PmjpvapcU7euxcbJplJBnRUfF99jHH9MSKk8dFRj34cBx4lKAQo8aG9lRj_8g-7HKeZnqPQyx-uMUBkSC1THkShiWx5jjjSeslM5l1Mu5ZS5nHIup5yN5aKhzA4PGP8a_0_0fhHtKWf-54pWxggvtXoCnQadEA</recordid><startdate>20120301</startdate><enddate>20120301</enddate><creator>Morris, Nancy A.</creator><creator>Slocum, Lee Ann</creator><general>Springer Science+Business Media</general><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7QJ</scope><scope>7U4</scope><scope>7XB</scope><scope>88G</scope><scope>8AM</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGRYB</scope><scope>BHHNA</scope><scope>CCPQU</scope><scope>DWI</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HEHIP</scope><scope>K7.</scope><scope>M0O</scope><scope>M2M</scope><scope>M2S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>WZK</scope></search><sort><creationdate>20120301</creationdate><title>Estimating Country-Level Terrorism Trends Using Group-Based Trajectory Analyses: Latent Class Growth Analysis and General Mixture Modeling</title><author>Morris, Nancy A. ; Slocum, Lee Ann</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c370t-a95c4bbe0f125847af3159bf6376d10177400a70bf9a42993b8dcf8fed82db3a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Analytical estimating</topic><topic>Countries</topic><topic>Criminology</topic><topic>Criminology and Criminal Justice</topic><topic>Law and Criminology</topic><topic>Measurement</topic><topic>Methodology</topic><topic>Methodology of the Social Sciences</topic><topic>Mixtures</topic><topic>Modeling</topic><topic>Original Paper</topic><topic>Parametric models</topic><topic>Research methods</topic><topic>Robustness</topic><topic>Sociology</topic><topic>Statistical discrepancies</topic><topic>Statistics</topic><topic>Terrorism</topic><topic>Trajectories</topic><topic>Violent crimes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Morris, Nancy A.</creatorcontrib><creatorcontrib>Slocum, Lee Ann</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Sociological Abstracts (pre-2017)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Psychology Database (Alumni)</collection><collection>Criminal Justice Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Criminology Collection</collection><collection>Sociological Abstracts</collection><collection>ProQuest One Community College</collection><collection>Sociological Abstracts</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Sociology Collection</collection><collection>ProQuest Criminal Justice (Alumni)</collection><collection>ProQuest Criminal Justice</collection><collection>ProQuest Psychology</collection><collection>Sociology Database (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>Sociological Abstracts (Ovid)</collection><jtitle>Journal of quantitative criminology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Morris, Nancy A.</au><au>Slocum, Lee Ann</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimating Country-Level Terrorism Trends Using Group-Based Trajectory Analyses: Latent Class Growth Analysis and General Mixture Modeling</atitle><jtitle>Journal of quantitative criminology</jtitle><stitle>J Quant Criminol</stitle><date>2012-03-01</date><risdate>2012</risdate><volume>28</volume><issue>1</issue><spage>103</spage><epage>139</epage><pages>103-139</pages><issn>0748-4518</issn><eissn>1573-7799</eissn><coden>JQCRE6</coden><abstract>Recent criminological research has used latent class growth analysis (LCGA), a form of group-based trajectory analysis, to identify distinct terrorism trends and areas of high terrorism activity at the country-level. The current study contributes to the literature by assessing the robustness of recent findings generated by one type of group-based analysis, LCGA, to changes in measurement and statistical methodology. Using data from the Global Terrorism Database (GTD), we consider the challenges and advantages of applying group-based analysis to macro-level terrorism data. We summarize and classify country-level patterns of domestic and transnational terrorism using two types of group-based analyses, LCGA and an alternative yet similar modeling approach, general mixture modeling (GMM). We evaluate the results from each approach using both substantive and empirical criteria, highlighting the similarities and differences provided by both techniques. We conclude that both group-based models have utility for terrorism research, yet for the purposes of identifying hot spots of terrorist activity, LCGA results provide greater policy utility.</abstract><cop>Boston</cop><pub>Springer Science+Business Media</pub><doi>10.1007/s10940-011-9158-2</doi><tpages>37</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0748-4518 |
| ispartof | Journal of quantitative criminology, 2012-03, Vol.28 (1), p.103-139 |
| issn | 0748-4518 1573-7799 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1030904972 |
| source | Applied Social Sciences Index & Abstracts (ASSIA); Jstor Complete Legacy; SpringerLink Journals; HeinOnline Law Journal Library; Sociological Abstracts |
| subjects | Analytical estimating Countries Criminology Criminology and Criminal Justice Law and Criminology Measurement Methodology Methodology of the Social Sciences Mixtures Modeling Original Paper Parametric models Research methods Robustness Sociology Statistical discrepancies Statistics Terrorism Trajectories Violent crimes |
| title | Estimating Country-Level Terrorism Trends Using Group-Based Trajectory Analyses: Latent Class Growth Analysis and General Mixture Modeling |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-29T04%3A13%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Estimating%20Country-Level%20Terrorism%20Trends%20Using%20Group-Based%20Trajectory%20Analyses:%20Latent%20Class%20Growth%20Analysis%20and%20General%20Mixture%20Modeling&rft.jtitle=Journal%20of%20quantitative%20criminology&rft.au=Morris,%20Nancy%20A.&rft.date=2012-03-01&rft.volume=28&rft.issue=1&rft.spage=103&rft.epage=139&rft.pages=103-139&rft.issn=0748-4518&rft.eissn=1573-7799&rft.coden=JQCRE6&rft_id=info:doi/10.1007/s10940-011-9158-2&rft_dat=%3Cjstor_proqu%3E43551924%3C/jstor_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=921578513&rft_id=info:pmid/&rft_jstor_id=43551924&rfr_iscdi=true |