Loading…
Confidence interval for normal means in meta-analysis based on a pretest estimator
Meta-analysis is a statistical method to summarize quantitative results from a set of published studies. Recently, a frequentist estimator was proposed for individual studies’ means in terms of the pretest (preliminary test) estimator. However, the confidence interval has not been considered yet for...
Saved in:
Published in: | Japanese journal of statistics and data science 2024-06, Vol.7 (1), p.537-568 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c291t-904bed23cd0209970bf51efd5a55c2118abf5086095b420c2552f756fe3997d23 |
---|---|
cites | cdi_FETCH-LOGICAL-c291t-904bed23cd0209970bf51efd5a55c2118abf5086095b420c2552f756fe3997d23 |
container_end_page | 568 |
container_issue | 1 |
container_start_page | 537 |
container_title | Japanese journal of statistics and data science |
container_volume | 7 |
creator | Taketomi, Nanami Chang, Yuan-Tsung Konno, Yoshihiko Mori, Mihoko Emura, Takeshi |
description | Meta-analysis is a statistical method to summarize quantitative results from a set of published studies. Recently, a frequentist estimator was proposed for individual studies’ means in terms of the pretest (preliminary test) estimator. However, the confidence interval has not been considered yet for the pretest estimator for meta-analysis. In this paper, a novel approach to construct a CI is considered based on the pretest estimator for meta-analysis. By pivoting the cumulative distribution function of the pretest estimator, we define an explicit formula of the CI. Furthermore, we show that the coverage probability of the CI controls the nominal confidence level both theoretically and numerically. To facilitate the proposed estimator and CI, we have implemented the computational tools in the R package “
meta.shrinkage
”. Finally, three datasets are analyzed to illustrate the proposed CI in real meta-analyses. The R code to produce all the numerical results of the paper is given in Supplementary Materials. |
doi_str_mv | 10.1007/s42081-023-00221-2 |
format | article |
fullrecord | <record><control><sourceid>crossref_sprin</sourceid><recordid>TN_cdi_crossref_primary_10_1007_s42081_023_00221_2</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_1007_s42081_023_00221_2</sourcerecordid><originalsourceid>FETCH-LOGICAL-c291t-904bed23cd0209970bf51efd5a55c2118abf5086095b420c2552f756fe3997d23</originalsourceid><addsrcrecordid>eNp9UNtKAzEQDaJgqf0Bn_ID0cnsZi-PUrxBQRB9DtndRLZsk5JZhf69Uys--jDMYeacYc4R4lrDjQaob6lEaLQCLBQAolZ4JhZoEFRTV-X5HzbVpVgRbYFZdVHW2CzE6zrFMA4-9l6Ocfb5y00ypCxjyjuGO-8i8YbB7JSLbjrQSLJz5AeZonRyn_3saZZc487NKV-Ji-Am8qvfvhTvD_dv6ye1eXl8Xt9tVI-tnlULZecHLPoBENq2hi4Y7cNgnDE9at04HkBTQWs6NtijMRjYQ_AFs1m4FHi62-dElH2w-8wf5IPVYI_B2FMwloOxP8HYo6g4iYjJ8cNnu02fmW3Rf6pvX9Vl4A</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Confidence interval for normal means in meta-analysis based on a pretest estimator</title><source>Springer Nature</source><creator>Taketomi, Nanami ; Chang, Yuan-Tsung ; Konno, Yoshihiko ; Mori, Mihoko ; Emura, Takeshi</creator><creatorcontrib>Taketomi, Nanami ; Chang, Yuan-Tsung ; Konno, Yoshihiko ; Mori, Mihoko ; Emura, Takeshi</creatorcontrib><description>Meta-analysis is a statistical method to summarize quantitative results from a set of published studies. Recently, a frequentist estimator was proposed for individual studies’ means in terms of the pretest (preliminary test) estimator. However, the confidence interval has not been considered yet for the pretest estimator for meta-analysis. In this paper, a novel approach to construct a CI is considered based on the pretest estimator for meta-analysis. By pivoting the cumulative distribution function of the pretest estimator, we define an explicit formula of the CI. Furthermore, we show that the coverage probability of the CI controls the nominal confidence level both theoretically and numerically. To facilitate the proposed estimator and CI, we have implemented the computational tools in the R package “
meta.shrinkage
”. Finally, three datasets are analyzed to illustrate the proposed CI in real meta-analyses. The R code to produce all the numerical results of the paper is given in Supplementary Materials.</description><identifier>ISSN: 2520-8756</identifier><identifier>EISSN: 2520-8764</identifier><identifier>DOI: 10.1007/s42081-023-00221-2</identifier><language>eng</language><publisher>Singapore: Springer Nature Singapore</publisher><subject>Chemistry and Earth Sciences ; Computer Science ; Economics ; Finance ; Health Sciences ; Humanities ; Insurance ; Law ; Management ; Mathematics and Statistics ; Medicine ; Original Paper ; Physics ; Statistical Theory and Methods ; Statistics ; Statistics and Computing/Statistics Programs ; Statistics for Business ; Statistics for Engineering ; Statistics for Life Sciences ; Statistics for Social Sciences</subject><ispartof>Japanese journal of statistics and data science, 2024-06, Vol.7 (1), p.537-568</ispartof><rights>The Author(s) under exclusive licence to Japanese Federation of Statistical Science Associations 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-904bed23cd0209970bf51efd5a55c2118abf5086095b420c2552f756fe3997d23</citedby><cites>FETCH-LOGICAL-c291t-904bed23cd0209970bf51efd5a55c2118abf5086095b420c2552f756fe3997d23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27922,27923</link.rule.ids></links><search><creatorcontrib>Taketomi, Nanami</creatorcontrib><creatorcontrib>Chang, Yuan-Tsung</creatorcontrib><creatorcontrib>Konno, Yoshihiko</creatorcontrib><creatorcontrib>Mori, Mihoko</creatorcontrib><creatorcontrib>Emura, Takeshi</creatorcontrib><title>Confidence interval for normal means in meta-analysis based on a pretest estimator</title><title>Japanese journal of statistics and data science</title><addtitle>Jpn J Stat Data Sci</addtitle><description>Meta-analysis is a statistical method to summarize quantitative results from a set of published studies. Recently, a frequentist estimator was proposed for individual studies’ means in terms of the pretest (preliminary test) estimator. However, the confidence interval has not been considered yet for the pretest estimator for meta-analysis. In this paper, a novel approach to construct a CI is considered based on the pretest estimator for meta-analysis. By pivoting the cumulative distribution function of the pretest estimator, we define an explicit formula of the CI. Furthermore, we show that the coverage probability of the CI controls the nominal confidence level both theoretically and numerically. To facilitate the proposed estimator and CI, we have implemented the computational tools in the R package “
meta.shrinkage
”. Finally, three datasets are analyzed to illustrate the proposed CI in real meta-analyses. The R code to produce all the numerical results of the paper is given in Supplementary Materials.</description><subject>Chemistry and Earth Sciences</subject><subject>Computer Science</subject><subject>Economics</subject><subject>Finance</subject><subject>Health Sciences</subject><subject>Humanities</subject><subject>Insurance</subject><subject>Law</subject><subject>Management</subject><subject>Mathematics and Statistics</subject><subject>Medicine</subject><subject>Original Paper</subject><subject>Physics</subject><subject>Statistical Theory and Methods</subject><subject>Statistics</subject><subject>Statistics and Computing/Statistics Programs</subject><subject>Statistics for Business</subject><subject>Statistics for Engineering</subject><subject>Statistics for Life Sciences</subject><subject>Statistics for Social Sciences</subject><issn>2520-8756</issn><issn>2520-8764</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9UNtKAzEQDaJgqf0Bn_ID0cnsZi-PUrxBQRB9DtndRLZsk5JZhf69Uys--jDMYeacYc4R4lrDjQaob6lEaLQCLBQAolZ4JhZoEFRTV-X5HzbVpVgRbYFZdVHW2CzE6zrFMA4-9l6Ocfb5y00ypCxjyjuGO-8i8YbB7JSLbjrQSLJz5AeZonRyn_3saZZc487NKV-Ji-Am8qvfvhTvD_dv6ye1eXl8Xt9tVI-tnlULZecHLPoBENq2hi4Y7cNgnDE9at04HkBTQWs6NtijMRjYQ_AFs1m4FHi62-dElH2w-8wf5IPVYI_B2FMwloOxP8HYo6g4iYjJ8cNnu02fmW3Rf6pvX9Vl4A</recordid><startdate>20240601</startdate><enddate>20240601</enddate><creator>Taketomi, Nanami</creator><creator>Chang, Yuan-Tsung</creator><creator>Konno, Yoshihiko</creator><creator>Mori, Mihoko</creator><creator>Emura, Takeshi</creator><general>Springer Nature Singapore</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20240601</creationdate><title>Confidence interval for normal means in meta-analysis based on a pretest estimator</title><author>Taketomi, Nanami ; Chang, Yuan-Tsung ; Konno, Yoshihiko ; Mori, Mihoko ; Emura, Takeshi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-904bed23cd0209970bf51efd5a55c2118abf5086095b420c2552f756fe3997d23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Chemistry and Earth Sciences</topic><topic>Computer Science</topic><topic>Economics</topic><topic>Finance</topic><topic>Health Sciences</topic><topic>Humanities</topic><topic>Insurance</topic><topic>Law</topic><topic>Management</topic><topic>Mathematics and Statistics</topic><topic>Medicine</topic><topic>Original Paper</topic><topic>Physics</topic><topic>Statistical Theory and Methods</topic><topic>Statistics</topic><topic>Statistics and Computing/Statistics Programs</topic><topic>Statistics for Business</topic><topic>Statistics for Engineering</topic><topic>Statistics for Life Sciences</topic><topic>Statistics for Social Sciences</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Taketomi, Nanami</creatorcontrib><creatorcontrib>Chang, Yuan-Tsung</creatorcontrib><creatorcontrib>Konno, Yoshihiko</creatorcontrib><creatorcontrib>Mori, Mihoko</creatorcontrib><creatorcontrib>Emura, Takeshi</creatorcontrib><collection>CrossRef</collection><jtitle>Japanese journal of statistics and data science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Taketomi, Nanami</au><au>Chang, Yuan-Tsung</au><au>Konno, Yoshihiko</au><au>Mori, Mihoko</au><au>Emura, Takeshi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Confidence interval for normal means in meta-analysis based on a pretest estimator</atitle><jtitle>Japanese journal of statistics and data science</jtitle><stitle>Jpn J Stat Data Sci</stitle><date>2024-06-01</date><risdate>2024</risdate><volume>7</volume><issue>1</issue><spage>537</spage><epage>568</epage><pages>537-568</pages><issn>2520-8756</issn><eissn>2520-8764</eissn><abstract>Meta-analysis is a statistical method to summarize quantitative results from a set of published studies. Recently, a frequentist estimator was proposed for individual studies’ means in terms of the pretest (preliminary test) estimator. However, the confidence interval has not been considered yet for the pretest estimator for meta-analysis. In this paper, a novel approach to construct a CI is considered based on the pretest estimator for meta-analysis. By pivoting the cumulative distribution function of the pretest estimator, we define an explicit formula of the CI. Furthermore, we show that the coverage probability of the CI controls the nominal confidence level both theoretically and numerically. To facilitate the proposed estimator and CI, we have implemented the computational tools in the R package “
meta.shrinkage
”. Finally, three datasets are analyzed to illustrate the proposed CI in real meta-analyses. The R code to produce all the numerical results of the paper is given in Supplementary Materials.</abstract><cop>Singapore</cop><pub>Springer Nature Singapore</pub><doi>10.1007/s42081-023-00221-2</doi><tpages>32</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2520-8756 |
ispartof | Japanese journal of statistics and data science, 2024-06, Vol.7 (1), p.537-568 |
issn | 2520-8756 2520-8764 |
language | eng |
recordid | cdi_crossref_primary_10_1007_s42081_023_00221_2 |
source | Springer Nature |
subjects | Chemistry and Earth Sciences Computer Science Economics Finance Health Sciences Humanities Insurance Law Management Mathematics and Statistics Medicine Original Paper Physics Statistical Theory and Methods Statistics Statistics and Computing/Statistics Programs Statistics for Business Statistics for Engineering Statistics for Life Sciences Statistics for Social Sciences |
title | Confidence interval for normal means in meta-analysis based on a pretest estimator |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T18%3A56%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_sprin&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Confidence%20interval%20for%20normal%20means%20in%20meta-analysis%20based%20on%20a%20pretest%20estimator&rft.jtitle=Japanese%20journal%20of%20statistics%20and%20data%20science&rft.au=Taketomi,%20Nanami&rft.date=2024-06-01&rft.volume=7&rft.issue=1&rft.spage=537&rft.epage=568&rft.pages=537-568&rft.issn=2520-8756&rft.eissn=2520-8764&rft_id=info:doi/10.1007/s42081-023-00221-2&rft_dat=%3Ccrossref_sprin%3E10_1007_s42081_023_00221_2%3C/crossref_sprin%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c291t-904bed23cd0209970bf51efd5a55c2118abf5086095b420c2552f756fe3997d23%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |