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Assessing Heterogeneity in Meta-Analysis: Q Statistic or I 2 Index?
In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the Q test. However, the Q test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the I 2...
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| Published in: | Psychological methods 2006-06, Vol.11 (2), p.193-206 |
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| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
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| container_end_page | 206 |
| container_issue | 2 |
| container_start_page | 193 |
| container_title | Psychological methods |
| container_volume | 11 |
| creator | Huedo-Medina, Tania B Sánchez-Meca, Julio Marín-Martínez, Fulgencio Botella, Juan |
| description | In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the
Q
test. However, the
Q
test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the
I
2
index has been proposed to quantify the degree of heterogeneity in a meta-analysis. In this article, the performances of the
Q
test and the confidence interval around the
I
2
index are compared by means of a Monte Carlo simulation. The results show the utility of the
I
2
index as a complement to the
Q
test, although it has the same problems of power with a small number of studies. |
| doi_str_mv | 10.1037/1082-989X.11.2.193 |
| format | article |
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Q
test. However, the
Q
test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the
I
2
index has been proposed to quantify the degree of heterogeneity in a meta-analysis. In this article, the performances of the
Q
test and the confidence interval around the
I
2
index are compared by means of a Monte Carlo simulation. The results show the utility of the
I
2
index as a complement to the
Q
test, although it has the same problems of power with a small number of studies.</description><identifier>ISSN: 1082-989X</identifier><identifier>EISSN: 1939-1463</identifier><identifier>DOI: 10.1037/1082-989X.11.2.193</identifier><language>eng</language><publisher>American Psychological Association</publisher><ispartof>Psychological methods, 2006-06, Vol.11 (2), p.193-206</ispartof><rights>2006 American Psychological Association</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><creatorcontrib>Huedo-Medina, Tania B</creatorcontrib><creatorcontrib>Sánchez-Meca, Julio</creatorcontrib><creatorcontrib>Marín-Martínez, Fulgencio</creatorcontrib><creatorcontrib>Botella, Juan</creatorcontrib><title>Assessing Heterogeneity in Meta-Analysis: Q Statistic or I 2 Index?</title><title>Psychological methods</title><description>In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the
Q
test. However, the
Q
test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the
I
2
index has been proposed to quantify the degree of heterogeneity in a meta-analysis. In this article, the performances of the
Q
test and the confidence interval around the
I
2
index are compared by means of a Monte Carlo simulation. The results show the utility of the
I
2
index as a complement to the
Q
test, although it has the same problems of power with a small number of studies.</description><issn>1082-989X</issn><issn>1939-1463</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid/><recordid>eNo1jzFPwzAQhS0EEqXwB5gyMLA43MWXxh6jCihSEQtIbJFjn6ugEqqel_x7IkGX977h6ZOeUrcIJYJpHhBspZ11nyViWZXozJlazOk00sqcz3waXKorkS8AJGNpoe5bERYZxl2x4czHnx2PPOSpGMbilbPX7ej3kwxyrS6S3wvf_PdSfTw9vq83evv2_LJut9ojUtbE0ZIPxIEZvPM2QEpENpLvsSdTcaxNihCBIoRVbZsU6xh6B9ZaaJJZqrs_rz_47iBT8Mc8hD1L9825Q-yqbv5lfgE3aETK</recordid><startdate>200606</startdate><enddate>200606</enddate><creator>Huedo-Medina, Tania B</creator><creator>Sánchez-Meca, Julio</creator><creator>Marín-Martínez, Fulgencio</creator><creator>Botella, Juan</creator><general>American Psychological Association</general><scope/></search><sort><creationdate>200606</creationdate><title>Assessing Heterogeneity in Meta-Analysis</title><author>Huedo-Medina, Tania B ; Sánchez-Meca, Julio ; Marín-Martínez, Fulgencio ; Botella, Juan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a114t-4ed84ac4ecee0a9a8c0ff448d4ab1b432ed53fd0d04d0c6587fd5dcb9088807f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huedo-Medina, Tania B</creatorcontrib><creatorcontrib>Sánchez-Meca, Julio</creatorcontrib><creatorcontrib>Marín-Martínez, Fulgencio</creatorcontrib><creatorcontrib>Botella, Juan</creatorcontrib><jtitle>Psychological methods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Huedo-Medina, Tania B</au><au>Sánchez-Meca, Julio</au><au>Marín-Martínez, Fulgencio</au><au>Botella, Juan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing Heterogeneity in Meta-Analysis: Q Statistic or I 2 Index?</atitle><jtitle>Psychological methods</jtitle><date>2006-06</date><risdate>2006</risdate><volume>11</volume><issue>2</issue><spage>193</spage><epage>206</epage><pages>193-206</pages><issn>1082-989X</issn><eissn>1939-1463</eissn><abstract>In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the
Q
test. However, the
Q
test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the
I
2
index has been proposed to quantify the degree of heterogeneity in a meta-analysis. In this article, the performances of the
Q
test and the confidence interval around the
I
2
index are compared by means of a Monte Carlo simulation. The results show the utility of the
I
2
index as a complement to the
Q
test, although it has the same problems of power with a small number of studies.</abstract><pub>American Psychological Association</pub><doi>10.1037/1082-989X.11.2.193</doi><tpages>14</tpages></addata></record> |
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| issn | 1082-989X 1939-1463 |
| language | eng |
| recordid | cdi_apa_psycarticles_met_11_2_193 |
| source | PsycARTICLES |
| title | Assessing Heterogeneity in Meta-Analysis: Q Statistic or I 2 Index? |
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