One‐sample aggregate data meta‐analysis of medians
An aggregate data meta‐analysis is a statistical method that pools the summary statistics of several selected studies to estimate the outcome of interest. When considering a continuous outcome, typically each study must report the same measure of the outcome variable and its spread (eg, the sample m...
Gespeichert in:
| Veröffentlicht in: | Statistics in medicine Jg. 38; H. 6; S. 969 - 984 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
England
Wiley Subscription Services, Inc
15.03.2019
|
| Schlagworte: | |
| ISSN: | 0277-6715, 1097-0258, 1097-0258 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | An aggregate data meta‐analysis is a statistical method that pools the summary statistics of several selected studies to estimate the outcome of interest. When considering a continuous outcome, typically each study must report the same measure of the outcome variable and its spread (eg, the sample mean and its standard error). However, some studies may instead report the median along with various measures of spread. Recently, the task of incorporating medians in meta‐analysis has been achieved by estimating the sample mean and its standard error from each study that reports a median in order to meta‐analyze the means. In this paper, we propose two alternative approaches to meta‐analyze data that instead rely on medians. We systematically compare these approaches via simulation study to each other and to methods that transform the study‐specific medians and spread into sample means and their standard errors. We demonstrate that the proposed median‐based approaches perform better than the transformation‐based approaches, especially when applied to skewed data and data with high inter‐study variance. Finally, we illustrate these approaches in a meta‐analysis of patient delay in tuberculosis diagnosis. |
|---|---|
| AbstractList | An aggregate data meta-analysis is a statistical method that pools the summary statistics of several selected studies to estimate the outcome of interest. When considering a continuous outcome, typically each study must report the same measure of the outcome variable and its spread (eg, the sample mean and its standard error). However, some studies may instead report the median along with various measures of spread. Recently, the task of incorporating medians in meta-analysis has been achieved by estimating the sample mean and its standard error from each study that reports a median in order to meta-analyze the means. In this paper, we propose two alternative approaches to meta-analyze data that instead rely on medians. We systematically compare these approaches via simulation study to each other and to methods that transform the study-specific medians and spread into sample means and their standard errors. We demonstrate that the proposed median-based approaches perform better than the transformation-based approaches, especially when applied to skewed data and data with high inter-study variance. Finally, we illustrate these approaches in a meta-analysis of patient delay in tuberculosis diagnosis. An aggregate data meta-analysis is a statistical method that pools the summary statistics of several selected studies to estimate the outcome of interest. When considering a continuous outcome, typically each study must report the same measure of the outcome variable and its spread (eg, the sample mean and its standard error). However, some studies may instead report the median along with various measures of spread. Recently, the task of incorporating medians in meta-analysis has been achieved by estimating the sample mean and its standard error from each study that reports a median in order to meta-analyze the means. In this paper, we propose two alternative approaches to meta-analyze data that instead rely on medians. We systematically compare these approaches via simulation study to each other and to methods that transform the study-specific medians and spread into sample means and their standard errors. We demonstrate that the proposed median-based approaches perform better than the transformation-based approaches, especially when applied to skewed data and data with high inter-study variance. Finally, we illustrate these approaches in a meta-analysis of patient delay in tuberculosis diagnosis.An aggregate data meta-analysis is a statistical method that pools the summary statistics of several selected studies to estimate the outcome of interest. When considering a continuous outcome, typically each study must report the same measure of the outcome variable and its spread (eg, the sample mean and its standard error). However, some studies may instead report the median along with various measures of spread. Recently, the task of incorporating medians in meta-analysis has been achieved by estimating the sample mean and its standard error from each study that reports a median in order to meta-analyze the means. In this paper, we propose two alternative approaches to meta-analyze data that instead rely on medians. We systematically compare these approaches via simulation study to each other and to methods that transform the study-specific medians and spread into sample means and their standard errors. We demonstrate that the proposed median-based approaches perform better than the transformation-based approaches, especially when applied to skewed data and data with high inter-study variance. Finally, we illustrate these approaches in a meta-analysis of patient delay in tuberculosis diagnosis. |
| Author | Benedetti, Andrea Zhao, XiaoFei McGrath, Sean Steele, Russell Qin, Zhi Zhen |
| Author_xml | – sequence: 1 givenname: Sean orcidid: 0000-0002-7281-3516 surname: McGrath fullname: McGrath, Sean organization: McGill University Health Centre – sequence: 2 givenname: XiaoFei surname: Zhao fullname: Zhao, XiaoFei organization: McGill University Health Centre – sequence: 3 givenname: Zhi Zhen surname: Qin fullname: Qin, Zhi Zhen organization: Stop TB Partnership Secretariat – sequence: 4 givenname: Russell surname: Steele fullname: Steele, Russell organization: McGill University – sequence: 5 givenname: Andrea orcidid: 0000-0002-8314-9497 surname: Benedetti fullname: Benedetti, Andrea email: andrea.benedetti@mcgill.ca organization: McGill University Health Centre |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30460713$$D View this record in MEDLINE/PubMed |
| BookMark | eNp10MtKxDAUBuAgI85FwSeQghs3HU-StmmXMngZGJmFug5pejpk6GVsWmR2PoLP6JOYuSmIbhJy8uVw8g9Jr6orJOScwpgCsGtrynEMlB-RAYVE-MDCuEcGwITwI0HDPhlauwSgNGTihPQ5BBEIygckmlf4-f5hVbkq0FOLRYML1aKXqVZ5JbbKXapKFWtrrFfnrpQZVdlTcpyrwuLZfh-Rl7vb58mDP5vfTyc3M1_zIOG-YBlPY8xSnessDVKMIU1RM3cWInCLFkjjVEOIXDHBBY0wpxGPqQAa0YSPyNWu76qpXzu0rSyN1VgUqsK6s5JRHoUh4xF39PIXXdZd40bfqBhYnMBWXexVl7q_yFVjStWs5SERB8Y7oJva2gZzqU2rWlNXbaNMISnITeTSRS43kf-M-P3g0PMP6u_omylw_a-TT9PHrf8CpkqPbw |
| CitedBy_id | crossref_primary_10_1016_j_jadohealth_2022_12_009 crossref_primary_10_1002_sim_8738 crossref_primary_10_1016_j_amjoto_2023_104195 crossref_primary_10_1002_pro6_1214 crossref_primary_10_3389_fpubh_2023_1183244 crossref_primary_10_3389_fcvm_2022_875327 crossref_primary_10_1016_j_wneu_2024_10_057 crossref_primary_10_1002_jrsm_1429 crossref_primary_10_1093_icvts_ivad003 crossref_primary_10_1016_j_oraloncology_2023_106415 crossref_primary_10_1136_emermed_2025_214918 crossref_primary_10_1002_lary_31148 crossref_primary_10_1002_hed_28174 crossref_primary_10_1002_jrsm_1686 crossref_primary_10_1097_MAO_0000000000004243 crossref_primary_10_1371_journal_pmed_1004110 crossref_primary_10_1097_GOX_0000000000006025 crossref_primary_10_3390_cancers12020477 crossref_primary_10_1016_j_ejphar_2021_173926 crossref_primary_10_1002_hed_27121 crossref_primary_10_1097_GOX_0000000000006026 crossref_primary_10_1016_j_clml_2022_11_002 crossref_primary_10_1016_j_ctarc_2025_100956 crossref_primary_10_1002_lary_32480 crossref_primary_10_1002_bimj_201900036 crossref_primary_10_1007_s00384_022_04144_4 crossref_primary_10_57264_cer_2023_0001 crossref_primary_10_1515_biol_2022_0559 crossref_primary_10_1155_2023_4477263 crossref_primary_10_1007_s00595_021_02446_8 crossref_primary_10_3389_fonc_2023_1088741 crossref_primary_10_1016_j_critrevonc_2020_103043 crossref_primary_10_1038_s41598_021_02770_6 crossref_primary_10_1016_j_euf_2021_04_003 crossref_primary_10_1002_alr_23512 crossref_primary_10_1002_ohn_1167 crossref_primary_10_1212_WN9_0000000000000030 crossref_primary_10_1371_journal_pdig_0000892 crossref_primary_10_1186_s12879_020_05524_3 crossref_primary_10_1016_j_forsciint_2023_111873 crossref_primary_10_1016_j_amjoto_2022_103517 crossref_primary_10_1016_j_euf_2023_03_004 crossref_primary_10_1002_pon_6064 crossref_primary_10_1007_s11060_025_05156_0 crossref_primary_10_1093_jncics_pkaf083 crossref_primary_10_1016_j_curtheres_2020_100607 crossref_primary_10_1016_j_euros_2022_04_009 crossref_primary_10_1016_j_tmaid_2020_101825 crossref_primary_10_1007_s00415_025_13204_y crossref_primary_10_1111_aor_14261 crossref_primary_10_1016_j_jclinepi_2020_05_010 crossref_primary_10_1097_GOX_0000000000005311 crossref_primary_10_1016_j_scitotenv_2021_148617 crossref_primary_10_1016_j_knee_2024_10_014 crossref_primary_10_1007_s12029_024_01152_1 crossref_primary_10_1007_s40120_025_00830_x crossref_primary_10_1186_s13045_023_01417_5 crossref_primary_10_1016_j_injury_2023_03_024 crossref_primary_10_1007_s00405_022_07490_9 crossref_primary_10_1177_02676591221096078 crossref_primary_10_1016_j_intimp_2021_108135 crossref_primary_10_3390_cancers13133206 crossref_primary_10_1111_apt_17370 crossref_primary_10_1016_j_oraloncology_2022_105809 crossref_primary_10_1093_cid_ciaf003 crossref_primary_10_1080_03007995_2022_2083326 crossref_primary_10_3390_jfmk10020126 crossref_primary_10_3390_ph14050476 crossref_primary_10_1016_j_scitotenv_2021_145755 crossref_primary_10_1186_s12931_021_01841_6 crossref_primary_10_1080_17476348_2021_1920927 crossref_primary_10_1007_s10654_020_00613_8 crossref_primary_10_3390_ijerph20166589 crossref_primary_10_1007_s00167_022_07204_y crossref_primary_10_1371_journal_pone_0287887 crossref_primary_10_1093_asj_sjae074 crossref_primary_10_1002_lary_32158 crossref_primary_10_1002_micr_30977 crossref_primary_10_3390_cancers16071425 crossref_primary_10_1016_S2468_1253_22_00346_6 crossref_primary_10_1002_hed_28251 crossref_primary_10_1007_s00266_024_04382_7 crossref_primary_10_3389_fonc_2023_1247879 crossref_primary_10_1016_j_ijporl_2024_111896 crossref_primary_10_1177_0962280219889080 crossref_primary_10_1002_alr_23367 crossref_primary_10_1016_j_ejca_2021_07_014 crossref_primary_10_1002_hed_27723 crossref_primary_10_1002_sim_9757 crossref_primary_10_1007_s00405_022_07589_z crossref_primary_10_1002_hed_27169 crossref_primary_10_1002_jmv_28677 crossref_primary_10_1016_j_amjoto_2023_104156 crossref_primary_10_1002_lary_31116 crossref_primary_10_1097_MAO_0000000000004446 crossref_primary_10_1111_tri_13753 crossref_primary_10_1002_lary_31751 crossref_primary_10_1038_s41586_023_06480_z crossref_primary_10_1177_15533506231209128 crossref_primary_10_1002_ohn_949 crossref_primary_10_1007_s00405_023_08191_7 crossref_primary_10_1007_s00432_022_03965_8 crossref_primary_10_1002_hed_27891 crossref_primary_10_1007_s00701_021_04794_3 crossref_primary_10_1017_ice_2020_1273 crossref_primary_10_1002_wjo2_70034 crossref_primary_10_1080_09638288_2021_2022781 crossref_primary_10_1016_S1470_2045_22_00271_6 crossref_primary_10_1093_nop_npab026 crossref_primary_10_1002_jca_21881 crossref_primary_10_1177_1747493020972922 crossref_primary_10_1016_j_eclinm_2025_103336 crossref_primary_10_1177_00034894251341110 crossref_primary_10_1177_09622802221139233 crossref_primary_10_2174_0109298673263933231206101556 crossref_primary_10_2217_fon_2020_0248 crossref_primary_10_1183_23120541_00195_2021 crossref_primary_10_3389_fonc_2020_00414 |
| Cites_doi | 10.1186/s12936-016-1635-5 10.1016/j.cct.2006.04.004 10.1186/1471-2288-5-13 10.1002/sim.4780151402 10.1038/bjc.2012.516 10.1186/s13049-014-0067-x 10.1016/0197-2456(86)90046-2 10.1002/sim.3607 10.1037/1082-989X.3.4.486 10.1093/biomet/52.3-4.591 10.1002/sim.1186 10.1186/1471-2288-14-135 10.1371/journal.pmed.1000326 10.1186/s12874-015-0055-5 10.5588/ijtld.13.0585 10.1186/1471-2334-9-91 10.1186/s12890-017-0551-y 10.6000/1929-6029.2015.04.01.6 10.1136/bmj.327.7414.557 10.1186/1475-2875-10-337 10.1007/s11222-013-9381-9 10.1186/2046-4053-2-10 10.1016/j.hpb.2016.05.001 10.1038/sj.bjc.6604096 10.3102/10769986030003261 10.1007/BF02589065 |
| ContentType | Journal Article |
| Copyright | 2018 John Wiley & Sons, Ltd. 2019 John Wiley & Sons, Ltd. |
| Copyright_xml | – notice: 2018 John Wiley & Sons, Ltd. – notice: 2019 John Wiley & Sons, Ltd. |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM K9. 7X8 |
| DOI | 10.1002/sim.8013 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Health & Medical Complete (Alumni) MEDLINE - Academic |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) ProQuest Health & Medical Complete (Alumni) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE ProQuest Health & Medical Complete (Alumni) CrossRef MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine Statistics Public Health |
| EISSN | 1097-0258 |
| EndPage | 984 |
| ExternalDocumentID | 30460713 10_1002_sim_8013 SIM8013 |
| Genre | article Research Support, Non-U.S. Gov't Journal Article |
| GrantInformation_xml | – fundername: Fonds de Recherche du Québec ‐ Santé – fundername: FRQS |
| GroupedDBID | --- .3N .GA 05W 0R~ 10A 123 1L6 1OB 1OC 1ZS 33P 3SF 3WU 4.4 4ZD 50Y 50Z 51W 51X 52M 52N 52O 52P 52S 52T 52U 52W 52X 5RE 5VS 66C 6PF 702 7PT 8-0 8-1 8-3 8-4 8-5 8UM 930 A03 AAESR AAEVG AAHHS AAHQN AAMNL AANLZ AAONW AASGY AAWTL AAXRX AAYCA AAZKR ABCQN ABCUV ABIJN ABJNI ABOCM ABPVW ACAHQ ACCFJ ACCZN ACGFS ACPOU ACXBN ACXQS ADBBV ADEOM ADIZJ ADKYN ADMGS ADOZA ADXAS ADZMN AEEZP AEIGN AEIMD AENEX AEQDE AEUQT AEUYR AFBPY AFFPM AFGKR AFPWT AFWVQ AFZJQ AHBTC AHMBA AITYG AIURR AIWBW AJBDE AJXKR ALAGY ALMA_UNASSIGNED_HOLDINGS ALUQN ALVPJ AMBMR AMYDB ATUGU AUFTA AZBYB AZVAB BAFTC BFHJK BHBCM BMNLL BMXJE BNHUX BROTX BRXPI BY8 CS3 D-E D-F DCZOG DPXWK DR2 DRFUL DRSTM DU5 EBD EBS EJD EMOBN F00 F01 F04 F5P G-S G.N GNP GODZA H.T H.X HBH HGLYW HHY HHZ HZ~ IX1 J0M JPC KQQ LATKE LAW LC2 LC3 LEEKS LH4 LITHE LOXES LP6 LP7 LUTES LYRES MEWTI MK4 MRFUL MRSTM MSFUL MSSTM MXFUL MXSTM N04 N05 N9A NF~ NNB O66 O9- OIG P2P P2W P2X P4D PALCI PQQKQ Q.N Q11 QB0 QRW R.K ROL RWI RX1 RYL SUPJJ SV3 TN5 UB1 V2E W8V W99 WBKPD WH7 WIB WIH WIK WJL WOHZO WQJ WRC WUP WWH WXSBR WYISQ XBAML XG1 XV2 ZZTAW ~IA ~WT AAMMB AAYXX AEFGJ AEYWJ AGHNM AGXDD AGYGG AIDQK AIDYY AMVHM CITATION O8X CGR CUY CVF ECM EIF NPM K9. 7X8 |
| ID | FETCH-LOGICAL-c3493-72d3b8edbcfcdb4be80bbec2bcf774cf7c7e18bc05e3a273716ef163817016193 |
| IEDL.DBID | DRFUL |
| ISICitedReferencesCount | 129 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000458895100006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0277-6715 1097-0258 |
| IngestDate | Fri Jul 11 11:47:10 EDT 2025 Tue Oct 07 05:46:52 EDT 2025 Mon Jul 21 06:03:50 EDT 2025 Sat Nov 29 05:32:42 EST 2025 Tue Nov 18 22:24:07 EST 2025 Wed Jan 22 16:25:04 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 6 |
| Keywords | meta-analysis median simulation study skewed data aggregate data |
| Language | English |
| License | 2018 John Wiley & Sons, Ltd. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c3493-72d3b8edbcfcdb4be80bbec2bcf774cf7c7e18bc05e3a273716ef163817016193 |
| Notes | ObjectType-Article-2 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Feature-3 ObjectType-Evidence Based Healthcare-1 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ORCID | 0000-0002-8314-9497 0000-0002-7281-3516 |
| PMID | 30460713 |
| PQID | 2180289063 |
| PQPubID | 48361 |
| PageCount | 1 |
| ParticipantIDs | proquest_miscellaneous_2136552363 proquest_journals_2180289063 pubmed_primary_30460713 crossref_citationtrail_10_1002_sim_8013 crossref_primary_10_1002_sim_8013 wiley_primary_10_1002_sim_8013_SIM8013 |
| PublicationCentury | 2000 |
| PublicationDate | 15 March 2019 |
| PublicationDateYYYYMMDD | 2019-03-15 |
| PublicationDate_xml | – month: 03 year: 2019 text: 15 March 2019 day: 15 |
| PublicationDecade | 2010 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England – name: New York |
| PublicationTitle | Statistics in medicine |
| PublicationTitleAlternate | Stat Med |
| PublicationYear | 2019 |
| Publisher | Wiley Subscription Services, Inc |
| Publisher_xml | – name: Wiley Subscription Services, Inc |
| References | 1965; 52 2015; 15 2015; 4 2013; 2 2013; 108 2016; 10 2011; 31 2008 2011; 10 2014; 24 2008; 98 2016; 18 2016; 15 1996; 15 1993; 2 2014; 22 2007; 28 2003; 327 1986; 7 2017; 17 2010; 29 2002; 21 2005; 5 2005; 30 2009; 9 2014; 14 1962 2016 1998; 3 2015 2014; 18 1980 2010; 7 e_1_2_8_28_1 e_1_2_8_29_1 e_1_2_8_24_1 Sohn H (e_1_2_8_16_1) 2016 e_1_2_8_27_1 e_1_2_8_3_1 Samal J (e_1_2_8_6_1) 2016; 10 e_1_2_8_2_1 e_1_2_8_5_1 e_1_2_8_4_1 Conover WJ (e_1_2_8_25_1) 1980 e_1_2_8_9_1 e_1_2_8_8_1 e_1_2_8_20_1 e_1_2_8_21_1 e_1_2_8_22_1 e_1_2_8_23_1 Kenney JF (e_1_2_8_26_1) 1962 e_1_2_8_17_1 e_1_2_8_18_1 e_1_2_8_19_1 e_1_2_8_13_1 e_1_2_8_14_1 e_1_2_8_35_1 Turchetti G (e_1_2_8_15_1) 2011; 31 Qin ZZ (e_1_2_8_7_1) 2015 e_1_2_8_32_1 O'Rourke K (e_1_2_8_34_1) 2008 e_1_2_8_10_1 e_1_2_8_31_1 e_1_2_8_11_1 e_1_2_8_12_1 e_1_2_8_33_1 e_1_2_8_30_1 |
| References_xml | – volume: 15 start-page: 593 issue: 1 year: 2016 article-title: The economics of malaria control and elimination: a systematic review publication-title: Malar J – volume: 9 start-page: 91 issue: 1 year: 2009 article-title: Time delays in diagnosis of pulmonary tuberculosis: a systematic review of literature publication-title: BMC Infect Dis – volume: 28 start-page: 105 issue: 2 year: 2007 end-page: 114 article-title: Random‐effects model for meta‐analysis of clinical trials: an update publication-title: Contemp Clin Trials – volume: 24 start-page: 461 issue: 3 year: 2014 end-page: 479 article-title: Linear quantile mixed models publication-title: Stat Comput – year: 1962 – volume: 2 start-page: 10 issue: 1 year: 2013 article-title: Survival of patients with non‐small cell lung cancer without treatment: a systematic review and meta‐analysis publication-title: Syst Rev – volume: 2 start-page: 269 year: 1993 end-page: 290 article-title: A comparison of procedures for combining risk differences in sets of 2 × 2 tables from clinical trials publication-title: J Italian Stat Soc – volume: 17 start-page: 202 issue: 1 year: 2017 article-title: Delay in diagnosis of pulmonary tuberculosis in low‐and middle‐income settings: systematic review and meta‐analysis publication-title: BMC Pulm Med – volume: 22 start-page: 67 year: 2014 article-title: The impact of direct admission to a catheterisation lab/CCU in patients with ST‐elevation myocardial infarction on the delay to reperfusion and early risk of death: results of a systematic review including meta‐analysis publication-title: Scand J Trauma Resusc Emerg Med – volume: 108 start-page: 39 issue: 1 year: 2013 end-page: 48 article-title: Evaluation of survival benefits by platinums and taxanes for an unfavourable subset of carcinoma of unknown primary: a systematic review and meta‐analysis publication-title: Br J Cancer – volume: 10 start-page: LE01 issue: 10 year: 2016 end-page: LE06 article-title: Health seeking behaviour among tuberculosis patients in India: a systematic review publication-title: J Clin Diagn Res – volume: 52 start-page: 591 issue: 3 year: 1965 end-page: 611 article-title: An analysis of variance test for normality publication-title: Biometrika – volume: 21 start-page: 1539 issue: 11 year: 2002 end-page: 1558 article-title: Quantifying heterogeneity in a meta‐analysis publication-title: Statist Med – volume: 14 start-page: 135 issue: 1 year: 2014 article-title: Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range publication-title: BMC Med Res Methodol – year: 2016 – volume: 18 start-page: 255 issue: 3 year: 2014 end-page: 266 article-title: Delays in diagnosis and treatment of pulmonary tuberculosis in India: a systematic review publication-title: Int J Tuberc Lung Dis – volume: 4 start-page: 57 issue: 1 year: 2015 end-page: 64 article-title: Estimating mean and standard deviation from the sample size, three quartiles, minimum, and maximum publication-title: Int J Stat Med Res – volume: 15 start-page: 61 issue: 1 year: 2015 article-title: Simulation‐based estimation of mean and standard deviation for meta‐analysis via approximate Bayesian computation (ABC) publication-title: BMC Med Res Methodol – volume: 3 start-page: 486 issue: 4 year: 1998 end-page: 504 article-title: Fixed‐ and random‐effects models in meta‐analysis publication-title: Psychol Methods – volume: 15 start-page: 1465 issue: 14 year: 1996 end-page: 1488 article-title: Simple robust procedures for combining risk differences in sets of 2 × 2 tables publication-title: Statist Med – volume: 18 start-page: 559 issue: 7 year: 2016 end-page: 566 article-title: Prognostic value of lymph node metastases detected during surgical exploration for pancreatic or periampullary cancer: a systematic review and meta‐analysis publication-title: HPB (Oxford) – volume: 31 start-page: 319 issue: 5 year: 2011 end-page: 327 article-title: Systematic review of the scientific literature on the economic evaluation of cochlear implants in adult patients publication-title: Acta Otorhinolaryngol Ital – volume: 327 start-page: 557 issue: 7414 year: 2003 end-page: 560 article-title: Measuring inconsistency in meta‐analyses publication-title: BMJ – volume: 5 start-page: 13 issue: 1 year: 2005 article-title: Estimating the mean and variance from the median, range, and the size of a sample publication-title: BMC Med Res Methodol – year: 1980 – year: 2008 – volume: 7 issue: 9 year: 2010 article-title: Seventy‐five trials and eleven systematic reviews a day: how will we ever keep up? publication-title: PLoS Med – volume: 98 start-page: 60 issue: 1 year: 2008 end-page: 70 article-title: Influences on pre‐hospital delay in the diagnosis of colorectal cancer: a systematic review publication-title: Br J Cancer – volume: 30 start-page: 261 issue: 3 year: 2005 end-page: 293 article-title: Bias and efficiency of meta‐analytic variance estimators in the random‐effects model publication-title: J Educ Behav Stat – volume: 7 start-page: 177 issue: 3 year: 1986 end-page: 188 article-title: Meta‐analysis in clinical trials publication-title: Control Clin Trials – volume: 29 start-page: 1259 issue: 12 year: 2010 end-page: 1265 article-title: Empirical vs natural weighting in random effects meta‐analysis publication-title: Statist Med – year: 2015 – volume: 10 start-page: 337 issue: 1 year: 2011 article-title: Costs and cost‐effectiveness of malaria control interventions‐a systematic review publication-title: Malar J – volume: 10 start-page: LE01 issue: 10 year: 2016 ident: e_1_2_8_6_1 article-title: Health seeking behaviour among tuberculosis patients in India: a systematic review publication-title: J Clin Diagn Res – ident: e_1_2_8_13_1 doi: 10.1186/s12936-016-1635-5 – ident: e_1_2_8_21_1 doi: 10.1016/j.cct.2006.04.004 – ident: e_1_2_8_17_1 doi: 10.1186/1471-2288-5-13 – ident: e_1_2_8_31_1 doi: 10.1002/sim.4780151402 – ident: e_1_2_8_10_1 doi: 10.1038/bjc.2012.516 – volume-title: Mathematics of Statistics, Part 1 year: 1962 ident: e_1_2_8_26_1 – ident: e_1_2_8_9_1 doi: 10.1186/s13049-014-0067-x – ident: e_1_2_8_24_1 doi: 10.1016/0197-2456(86)90046-2 – ident: e_1_2_8_30_1 doi: 10.1002/sim.3607 – ident: e_1_2_8_23_1 doi: 10.1037/1082-989X.3.4.486 – ident: e_1_2_8_27_1 doi: 10.1093/biomet/52.3-4.591 – ident: e_1_2_8_28_1 doi: 10.1002/sim.1186 – volume: 31 start-page: 319 issue: 5 year: 2011 ident: e_1_2_8_15_1 article-title: Systematic review of the scientific literature on the economic evaluation of cochlear implants in adult patients publication-title: Acta Otorhinolaryngol Ital – ident: e_1_2_8_18_1 doi: 10.1186/1471-2288-14-135 – ident: e_1_2_8_2_1 doi: 10.1371/journal.pmed.1000326 – ident: e_1_2_8_20_1 doi: 10.1186/s12874-015-0055-5 – ident: e_1_2_8_4_1 doi: 10.5588/ijtld.13.0585 – volume-title: Delays in Diagnosis and Treatment of Pulmonary Tuberculosis, and Patient Care‐Seeking Pathways in China: A Systematic Review and Meta‐Analysis year: 2015 ident: e_1_2_8_7_1 – volume-title: Practical Nonparametric Statistics year: 1980 ident: e_1_2_8_25_1 – ident: e_1_2_8_5_1 doi: 10.1186/1471-2334-9-91 – ident: e_1_2_8_3_1 doi: 10.1186/s12890-017-0551-y – ident: e_1_2_8_19_1 doi: 10.6000/1929-6029.2015.04.01.6 – volume-title: The Combining of Information: Investigating and Synthesizing What is Possibly Common in Clinical Observations or Studies via Likelihood year: 2008 ident: e_1_2_8_34_1 – ident: e_1_2_8_33_1 doi: 10.1136/bmj.327.7414.557 – volume-title: Improving Tuberculosis Diagnosis in Vulnerable Populations: Impact and Cost‐Effectiveness of Novel, Rapid Molecular Assays year: 2016 ident: e_1_2_8_16_1 – ident: e_1_2_8_14_1 doi: 10.1186/1475-2875-10-337 – ident: e_1_2_8_35_1 doi: 10.1007/s11222-013-9381-9 – ident: e_1_2_8_12_1 doi: 10.1186/2046-4053-2-10 – ident: e_1_2_8_11_1 doi: 10.1016/j.hpb.2016.05.001 – ident: e_1_2_8_8_1 doi: 10.1038/sj.bjc.6604096 – ident: e_1_2_8_22_1 doi: 10.3102/10769986030003261 – ident: e_1_2_8_29_1 – ident: e_1_2_8_32_1 doi: 10.1007/BF02589065 |
| SSID | ssj0011527 |
| Score | 2.6002312 |
| Snippet | An aggregate data meta‐analysis is a statistical method that pools the summary statistics of several selected studies to estimate the outcome of interest. When... An aggregate data meta-analysis is a statistical method that pools the summary statistics of several selected studies to estimate the outcome of interest. When... |
| SourceID | proquest pubmed crossref wiley |
| SourceType | Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 969 |
| SubjectTerms | aggregate data Computer Simulation Data Interpretation, Statistical Delayed Diagnosis - statistics & numerical data Humans median Medical research Medical statistics Meta-analysis Meta-Analysis as Topic Models, Statistical Sampling simulation study skewed data Statistical methods Statistics as Topic - methods Tuberculosis, Pulmonary - diagnosis |
| Title | One‐sample aggregate data meta‐analysis of medians |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fsim.8013 https://www.ncbi.nlm.nih.gov/pubmed/30460713 https://www.proquest.com/docview/2180289063 https://www.proquest.com/docview/2136552363 |
| Volume | 38 |
| WOSCitedRecordID | wos000458895100006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVWIB databaseName: Wiley Online Library Full Collection 2020 customDbUrl: eissn: 1097-0258 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0011527 issn: 0277-6715 databaseCode: DRFUL dateStart: 19960101 isFulltext: true titleUrlDefault: https://onlinelibrary.wiley.com providerName: Wiley-Blackwell |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3bSsQwEB10FRHEy3q_UUH0qbrbtE36KOqioKt4Y99KkqYiuF3Z7vrsJ_iNfokzvcmiguBLS8m0KZmZ5EwmOQHYFU3OI-Eq21dM24jAta0oSpGBjiWLfd_LyJ4fLni7LTqd4LpYVUl7YXJ-iGrCjTwj66_JwaVKD79IQ9On7gF2r2wcJhw0W68GEyc3rfuLKodQHthKSUqfN72SerbhHJbvjg5G3xDmKGDNRpzW3H_-dR5mC5xpHeWGsQBjJqnD1GWRSa_DTD5fZ-XbkOowTagzJ21eBP8qMR9v76kk6mBLPmJMTrNtFi0ntbpmILFQFmwmVi-2su0nSboE963Tu-MzuzhgwdbMDZjNnYgpYSKlYx0pVxnRUKhTB58RFeJFc9MUSjc8wyTiHIytTEwAjkjcMfJiy1BLeolZBYtWiypPRQ3tYsjoKRlLrqSrmeDSc7Rcg_2ypUNdsI_TIRjPYc6b7ITYRiG10RrsVJIvOePGDzKbpbLCwufS0CEyOxEg5sJPVMXoLZQCkYnpDUmGofU5jGRWciVXlWQ5Yk4f38t0-Wvt4e35Jd3X_yq4AdOIswJautb0NqE26A_NFkzqV9RrfxvGeUdsF9b7CRPn8jM |
| linkProvider | Wiley-Blackwell |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1bS8MwFD7MTXQgXub9WkH0qW5r2qbFJ1GH4jbFG3srSZqK4Dpx6rM_wd_oL_Gc3kRUEHxpKTltSs5J8p1zki8AW16T89CzpelKpkxE4MqU5KUIX0WCRa7rJGTPN23e7Xq9nn9egr18L0zKD1EE3KhnJOM1dXAKSNc_WUOHd_1dHF_ZCFRstCI078rhReu6XSQR8hNbKUvp8qaTc882rHr-7tfZ6BvE_IpYkymnNfWvn52GyQxpGvupacxAScc1GOtkufQaTKQROyPdiFSDKuHOlLZ5FtyzWL-_vg0FkQcb4ha9coq3GbSg1OjrJ4GFIuMzMQaRkWxAiYdzcN06ujo4NrMjFkzFbJ-Z3AqZ9HQoVaRCaUvtNSRq1cJnxIV4UVw3PakajmYCkQ56VzoiCEc07uh7sXkox4NYL4JB60WlI8OGstFpdKSIBJfCVszjwrGUWIKdvKkDlfGP0zEY90HKnGwF2EYBtdESbBaSDynnxg8yq7m2gqzXDQOL6Ow8H1EXfqIoxv5CSRAR68EzyTC0P4uRzEKq5aKSJEvM6ePbiTJ_rT24POnQffmvghswfnzVaQftk-7pClQRdfm0kK3prEL56fFZr8GoekEdP65nRvwB2yH1Ow |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3bSsQwEB10FRHEy3p31QqiT9Xdpm1afBJ1UdxdxRu-lSRNRdDust312U_wG_0SZ3oTUUHwpaVk2pRMJjmTSc4AbHsNzkPPlqYrmTIRgStTkpcifBUJFrmuk5I937V4p-Pd3_uXI3BQnIXJ-CHKBTeyjHS8JgPXvTDa_2QNTR6f93B8ZaMwZlMOmQqMHV81b1tlEKHI2EpRSpc3nIJ7tm7tF-9-nY2-QcyviDWdcpoz__rZWZjOkaZxmHWNORjRcRUm2nksvQpT2YqdkR1EqsIk4c6Mtnke3ItYv7--JYLIgw3xgF45rbcZtKHUeNYDgYUi5zMxupGRHkCJkwW4bZ7cHJ2aeYoFUzHbZya3QiY9HUoVqVDaUnt1iVq18BlxIV4U1w1PqrqjmUCkg96VjgjCEY07-l5sESpxN9bLYNB-UenIsK5sdBodKSLBpbAV87hwLCVWYLdo6kDl_OOUBuMpyJiTrQDbKKA2WoGtUrKXcW78IFMrtBXkVpcEFtHZeT6iLvxEWYz2QkEQEevukGQY9j-LkcxSpuWykjRKzOnjO6kyf609uD5r0331r4KbMHF53AxaZ53zNZhE0OXTPraGU4PKoD_U6zCuXlDF_Y28D38Adt_0tg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=One%E2%80%90sample+aggregate+data+meta%E2%80%90analysis+of+medians&rft.jtitle=Statistics+in+medicine&rft.au=McGrath%2C+Sean&rft.au=Zhao%2C+XiaoFei&rft.au=Qin%2C+Zhi+Zhen&rft.au=Steele%2C+Russell&rft.date=2019-03-15&rft.issn=0277-6715&rft.eissn=1097-0258&rft.volume=38&rft.issue=6&rft.spage=969&rft.epage=984&rft_id=info:doi/10.1002%2Fsim.8013&rft.externalDBID=10.1002%252Fsim.8013&rft.externalDocID=SIM8013 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0277-6715&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0277-6715&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0277-6715&client=summon |