Evaluation of the type I error rate when using parametric bootstrap analysis of a cluster randomized controlled trial with binary outcomes and a small number of clusters
•The type I error rate is inflated under scenarios of a small number of clusters per treatment in a cluster randomized trials when using parametric bootstrap.•When analyzing cluster randomized trials, the pbkrtest package is limited in performance as it resamples the observations ignoring clusters.•...
Saved in:
| Published in | Computer methods and programs in biomedicine Vol. 215; p. 106654 |
|---|---|
| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Ireland
Elsevier B.V
01.03.2022
|
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | •The type I error rate is inflated under scenarios of a small number of clusters per treatment in a cluster randomized trials when using parametric bootstrap.•When analyzing cluster randomized trials, the pbkrtest package is limited in performance as it resamples the observations ignoring clusters.•We want to highlight that while the well-known nesting/degrees of freedom issue undermines p-values when k <= 20, we show here that small number of clusters and small ICC inflate type I error rates, setting the nesting/df issue aside.
Cluster randomized controlled trials (cRCTs) are increasingly used but must be analyzed carefully. We conducted a simulation study to evaluate the validity of a parametric bootstrap (PB) approach with respect to the empirical type I error rate for a cRCT with binary outcomes and a small number of clusters.
We simulated a case study with a binary (0/1) outcome, four clusters, and 100 subjects per cluster. To compare the validity of the test with respect to error rate, we simulated the same experiment with K=10, 20, and 30 clusters, each with 2,000 simulated datasets. To test the null hypothesis, we used a generalized linear mixed model including a random intercept for clusters and obtained p-values based on likelihood ratio tests (LRTs) using the parametric bootstrap method as implemented in the R package “pbkrtest”.
The PB test produced error rates of 9.1%, 5.5%, 4.9%, and 5.0% on average across all ICC values for K=4, K=10, K=20, and K=30, respectively. The error rates were higher, ranging from 9.1% to 36.5% for K=4, in the models with singular fits (i.e., ignoring clustering) because the ICC was estimated to be zero.
Using the parametric bootstrap for cRCTs with a small number of clusters results in inflated error rates and is not valid |
|---|---|
| AbstractList | •The type I error rate is inflated under scenarios of a small number of clusters per treatment in a cluster randomized trials when using parametric bootstrap.•When analyzing cluster randomized trials, the pbkrtest package is limited in performance as it resamples the observations ignoring clusters.•We want to highlight that while the well-known nesting/degrees of freedom issue undermines p-values when k <= 20, we show here that small number of clusters and small ICC inflate type I error rates, setting the nesting/df issue aside.
Cluster randomized controlled trials (cRCTs) are increasingly used but must be analyzed carefully. We conducted a simulation study to evaluate the validity of a parametric bootstrap (PB) approach with respect to the empirical type I error rate for a cRCT with binary outcomes and a small number of clusters.
We simulated a case study with a binary (0/1) outcome, four clusters, and 100 subjects per cluster. To compare the validity of the test with respect to error rate, we simulated the same experiment with K=10, 20, and 30 clusters, each with 2,000 simulated datasets. To test the null hypothesis, we used a generalized linear mixed model including a random intercept for clusters and obtained p-values based on likelihood ratio tests (LRTs) using the parametric bootstrap method as implemented in the R package “pbkrtest”.
The PB test produced error rates of 9.1%, 5.5%, 4.9%, and 5.0% on average across all ICC values for K=4, K=10, K=20, and K=30, respectively. The error rates were higher, ranging from 9.1% to 36.5% for K=4, in the models with singular fits (i.e., ignoring clustering) because the ICC was estimated to be zero.
Using the parametric bootstrap for cRCTs with a small number of clusters results in inflated error rates and is not valid Cluster randomized controlled trials (cRCTs) are increasingly used but must be analyzed carefully. We conducted a simulation study to evaluate the validity of a parametric bootstrap (PB) approach with respect to the empirical type I error rate for a cRCT with binary outcomes and a small number of clusters.BACKGROUNDCluster randomized controlled trials (cRCTs) are increasingly used but must be analyzed carefully. We conducted a simulation study to evaluate the validity of a parametric bootstrap (PB) approach with respect to the empirical type I error rate for a cRCT with binary outcomes and a small number of clusters.We simulated a case study with a binary (0/1) outcome, four clusters, and 100 subjects per cluster. To compare the validity of the test with respect to error rate, we simulated the same experiment with K=10, 20, and 30 clusters, each with 2,000 simulated datasets. To test the null hypothesis, we used a generalized linear mixed model including a random intercept for clusters and obtained p-values based on likelihood ratio tests (LRTs) using the parametric bootstrap method as implemented in the R package "pbkrtest".METHODSWe simulated a case study with a binary (0/1) outcome, four clusters, and 100 subjects per cluster. To compare the validity of the test with respect to error rate, we simulated the same experiment with K=10, 20, and 30 clusters, each with 2,000 simulated datasets. To test the null hypothesis, we used a generalized linear mixed model including a random intercept for clusters and obtained p-values based on likelihood ratio tests (LRTs) using the parametric bootstrap method as implemented in the R package "pbkrtest".The PB test produced error rates of 9.1%, 5.5%, 4.9%, and 5.0% on average across all ICC values for K=4, K=10, K=20, and K=30, respectively. The error rates were higher, ranging from 9.1% to 36.5% for K=4, in the models with singular fits (i.e., ignoring clustering) because the ICC was estimated to be zero.RESULTSThe PB test produced error rates of 9.1%, 5.5%, 4.9%, and 5.0% on average across all ICC values for K=4, K=10, K=20, and K=30, respectively. The error rates were higher, ranging from 9.1% to 36.5% for K=4, in the models with singular fits (i.e., ignoring clustering) because the ICC was estimated to be zero.Using the parametric bootstrap for cRCTs with a small number of clusters results in inflated error rates and is not valid.CONCLUSIONUsing the parametric bootstrap for cRCTs with a small number of clusters results in inflated error rates and is not valid. Cluster randomized controlled trials (cRCTs) are increasingly used but must be analyzed carefully. We conducted a simulation study to evaluate the validity of a parametric bootstrap (PB) approach with respect to the empirical type I error rate for a cRCT with binary outcomes and a small number of clusters. We simulated a case study with a binary (0/1) outcome, four clusters, and 100 subjects per cluster. To compare the validity of the test with respect to error rate, we simulated the same experiment with K=10, 20, and 30 clusters, each with 2,000 simulated datasets. To test the null hypothesis, we used a generalized linear mixed model including a random intercept for clusters and obtained p-values based on likelihood ratio tests (LRTs) using the parametric bootstrap method as implemented in the R package "pbkrtest". The PB test produced error rates of 9.1%, 5.5%, 4.9%, and 5.0% on average across all ICC values for K=4, K=10, K=20, and K=30, respectively. The error rates were higher, ranging from 9.1% to 36.5% for K=4, in the models with singular fits (i.e., ignoring clustering) because the ICC was estimated to be zero. Using the parametric bootstrap for cRCTs with a small number of clusters results in inflated error rates and is not valid. |
| ArticleNumber | 106654 |
| Author | Jamshidi-Naeini, Yasaman Allison, David B. Golzarri-Arroyo, Lilian Brown, Andrew W. Li, Peng Oakes, J. Michael Dickinson, Stephanie L. Zoh, Roger S. Owora, Arthur H. |
| AuthorAffiliation | 2. Department of Applied Health Science, Indiana University School of Public Health-Bloomington 1. Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington 4. School of Public Health, University of Minnesota 3. School of Nursing, University of Alabama at Birmingham |
| AuthorAffiliation_xml | – name: 1. Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington – name: 2. Department of Applied Health Science, Indiana University School of Public Health-Bloomington – name: 3. School of Nursing, University of Alabama at Birmingham – name: 4. School of Public Health, University of Minnesota |
| Author_xml | – sequence: 1 givenname: Lilian surname: Golzarri-Arroyo fullname: Golzarri-Arroyo, Lilian email: lgolzarr@indiana.edu organization: Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington USA – sequence: 2 givenname: Stephanie L. surname: Dickinson fullname: Dickinson, Stephanie L. organization: Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington USA – sequence: 3 givenname: Yasaman surname: Jamshidi-Naeini fullname: Jamshidi-Naeini, Yasaman organization: Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington USA – sequence: 4 givenname: Roger S. surname: Zoh fullname: Zoh, Roger S. organization: Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington USA – sequence: 5 givenname: Andrew W. surname: Brown fullname: Brown, Andrew W. organization: Department of Applied Health Science, Indiana University School of Public Health-Bloomington USA – sequence: 6 givenname: Arthur H. surname: Owora fullname: Owora, Arthur H. organization: Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington USA – sequence: 7 givenname: Peng surname: Li fullname: Li, Peng organization: School of Nursing, University of Alabama at Birmingham USA – sequence: 8 givenname: J. Michael surname: Oakes fullname: Oakes, J. Michael organization: School of Public Health, University of Minnesota USA – sequence: 9 givenname: David B. surname: Allison fullname: Allison, David B. organization: Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35093646$$D View this record in MEDLINE/PubMed |
| BookMark | eNqFksFu1DAQQCNURLeFH-CAfOSSxXYSJ0EIqaoKVKrEBc7WxJl0vTh2sJ2tlj_iL3HYLYIeysmWZ96bkWfOshPrLGbZS0bXjDLxZrtW49StOeU8PQhRlU-yFWtqnteVqE6yVUpqcy5ofZqdhbCllPKqEs-y06KibSFKscp-Xu3AzBC1s8QNJG6QxP2E5Jqg984TDxHJ3QYtmYO2t2QCDyNGrxXpnIshepgIWDD7oMNiAKLMHCIuqO3dqH9gT5Sz0Ttj0jWhYMidjhvSaQt-T9wclRsxJE2f8DCCMcTOY5ccSXjUhefZ0wFMwBfH8zz7-uHqy-Wn_Obzx-vLi5tcVVTEvGn6blBN21YN41UJA9StEPXAVNH1okegqsSBtqosi3YA7BVDVQFXoms7BUNxnr0_eKe5G1MYU-tg5OT1mLqVDrT8N2L1Rt66nWyasi4YS4LXR4F332cMUY46KDQGLLo5SC54ySkr6yX11d-1_hS5n09KaA4JyrsQPA5S6fh7Wqm0NpJRuayC3MplFeSyCvKwCgnlD9B7-6PQuwOE6Yd3Gr0MSqNV2GuPKsre6cfxtw9wZbTVCsw33P8P_gUgc-bY |
| CitedBy_id | crossref_primary_10_1098_rstb_2022_0227 crossref_primary_10_1089_chi_2021_0207 crossref_primary_10_1371_journal_pone_0314705 crossref_primary_10_1002_oby_23373 crossref_primary_10_1016_j_eclinm_2022_101686 crossref_primary_10_2196_54090 |
| Cites_doi | 10.1007/s00431-020-03590-y 10.1186/1471-2288-9-37 10.2105/AJPH.94.3.423 10.3945/ajcn.114.105072 10.1186/1472-6963-4-33 10.1136/bmj.j3064 10.2105/AJPH.94.3.416 10.1080/00273171.2016.1167008 10.1089/chi.2019.0142 10.1089/chi.2016.0216 10.1111/j.1467-9868.2007.00593.x 10.1093/ije/dyx169 10.1186/s12874-015-0026-x 10.1002/1097-0258(20010215)20:3<453::AID-SIM803>3.0.CO;2-L 10.1177/0962280220932962 10.1177/0013164416678980 10.1111/j.1467-9876.2004.00428.x 10.1093/abm/kaz065 10.1177/1536867X1301300111 10.1186/s13063-016-1571-2 10.18637/jss.v059.i09 10.18637/jss.v067.i01 10.1002/sim.2731 |
| ContentType | Journal Article |
| Copyright | 2022 Elsevier B.V. Copyright © 2022 Elsevier B.V. All rights reserved. |
| Copyright_xml | – notice: 2022 Elsevier B.V. – notice: Copyright © 2022 Elsevier B.V. All rights reserved. |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 7X8 5PM |
| DOI | 10.1016/j.cmpb.2022.106654 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic PubMed Central (Full Participant titles) |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic MEDLINE |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1872-7565 |
| EndPage | 106654 |
| ExternalDocumentID | PMC8847311 35093646 10_1016_j_cmpb_2022_106654 S0169260722000396 |
| Genre | Randomized Controlled Trial Journal Article |
| GrantInformation_xml | – fundername: NIDDK NIH HHS grantid: R25 DK099080 – fundername: NIA NIH HHS grantid: U24 AG056053 – fundername: NIGMS NIH HHS grantid: R25 GM141507 – fundername: AHRQ HHS grantid: K12 HS026390 – fundername: NIA NIH HHS grantid: P30 AG050886 – fundername: NHLBI NIH HHS grantid: R25 HL124208 |
| GroupedDBID | --- --K --M -~X .1- .DC .FO .GJ .~1 0R~ 1B1 1P~ 1RT 1~. 1~5 29F 4.4 457 4G. 53G 5GY 5RE 5VS 7-5 71M 8P~ 9JN AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AATTM AAXKI AAXUO AAYFN AAYWO ABBOA ABFNM ABJNI ABMAC ABMZM ABWVN ABXDB ACDAQ ACGFS ACIEU ACIUM ACNNM ACRLP ACRPL ACVFH ACZNC ADBBV ADCNI ADEZE ADJOM ADMUD ADNMO AEBSH AEIPS AEKER AENEX AEUPX AEVXI AFJKZ AFPUW AFRHN AFTJW AFXIZ AGCQF AGHFR AGQPQ AGUBO AGYEJ AHHHB AHZHX AIALX AIEXJ AIGII AIIUN AIKHN AITUG AJRQY AJUYK AKBMS AKRWK AKYEP ALMA_UNASSIGNED_HOLDINGS AMRAJ ANKPU ANZVX AOUOD APXCP ASPBG AVWKF AXJTR AZFZN BKOJK BLXMC BNPGV CS3 DU5 EBS EFJIC EFKBS EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA GBOLZ HLZ HMK HMO HVGLF HZ~ IHE J1W KOM LG9 M29 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- ROL RPZ SAE SBC SDF SDG SEL SES SEW SPC SPCBC SSH SSV SSZ T5K UHS WUQ XPP Z5R ZGI ZY4 ~G- AACTN AAIAV ABLVK ABTAH ABYKQ AFKWA AJBFU AJOXV AMFUW EFLBG LCYCR RIG AAYXX AFCTW AGRNS CITATION CGR CUY CVF ECM EIF NPM 7X8 5PM |
| ID | FETCH-LOGICAL-c506t-88dbfc899581254afa79667f1c3bd6dea0c4ef09c4439faedc1ec5a2c6b9bcaf3 |
| IEDL.DBID | .~1 |
| ISSN | 0169-2607 1872-7565 |
| IngestDate | Thu Aug 21 18:38:51 EDT 2025 Sun Aug 24 04:04:07 EDT 2025 Mon Jul 21 05:45:08 EDT 2025 Tue Jul 01 02:41:14 EDT 2025 Thu Apr 24 22:54:18 EDT 2025 Fri Feb 23 02:41:23 EST 2024 Tue Aug 26 16:33:34 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Language | English |
| License | Copyright © 2022 Elsevier B.V. All rights reserved. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c506t-88dbfc899581254afa79667f1c3bd6dea0c4ef09c4439faedc1ec5a2c6b9bcaf3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 |
| OpenAccessLink | https://www.ncbi.nlm.nih.gov/pmc/articles/8847311 |
| PMID | 35093646 |
| PQID | 2624201471 |
| PQPubID | 23479 |
| PageCount | 1 |
| ParticipantIDs | pubmedcentral_primary_oai_pubmedcentral_nih_gov_8847311 proquest_miscellaneous_2624201471 pubmed_primary_35093646 crossref_citationtrail_10_1016_j_cmpb_2022_106654 crossref_primary_10_1016_j_cmpb_2022_106654 elsevier_sciencedirect_doi_10_1016_j_cmpb_2022_106654 elsevier_clinicalkey_doi_10_1016_j_cmpb_2022_106654 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2022-03-01 |
| PublicationDateYYYYMMDD | 2022-03-01 |
| PublicationDate_xml | – month: 03 year: 2022 text: 2022-03-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | Ireland |
| PublicationPlace_xml | – name: Ireland |
| PublicationTitle | Computer methods and programs in biomedicine |
| PublicationTitleAlternate | Comput Methods Programs Biomed |
| PublicationYear | 2022 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Bates (bib0030) 2015; 67 Health, N.I.o. Golzarri-Arroyo (bib0005) 2020; 179 Hayes, Moulton (bib0017) 2017 Halekoh, Højsgaard (bib0029) 2014; 59 Murray (bib0007) 1998 Huang (bib0026) 2018; 78 Science, P.S.E.C.o. Ng, Grieve, Carpenter (bib0025) 2013; 13 Murray, D.M., et al. Li, F., et al. Lorenz (bib0001) 2018; 115 Turner, Omar, Thompson (bib0034) 2001; 20 Leyrat (bib0013) 2017; 47 Aceves-Martins (bib0020) 2017; 13 Beasley (bib0031) 2004; 53 Donner, Klar (bib0003) 2004; 94 Kahan (bib0002) 2016; 17 Golzarri-Arroyo (bib0006) 2020; 16 Murray, Varnell, Blitstein (bib0010) 2004; 94 Davison, Hinkley (bib0024) 1997 Li, Redden (bib0008) 2015; 15 Brown (bib0011) 2015; 102 (1468-4357 (Electronic)). cited 2020; Available from Flynn, Peters (bib0023) 2004; 4 4/14/2021 [cited 2021 May 4th]; Available from Campbell, Walters (bib0012) 2014 Aceves-Martins (bib0021) 2017; 13 Campbell, Donner, Klar (bib0019) 2007; 26 Li (bib0016) 2021; 30 McNeish, Stapleton (bib0014) 2016; 51 (0277-6715 (Print)). Field, C.A. and A.H. Welsh 2007. 69(3): p. 369-390. . Tekwe, Allison (bib0004) 2020; 54 Hemming, K., et al. Brightwell (bib0027) 2013 Ma (bib0033) 2009; 9 2017. 358: p. j3064. Murray (10.1016/j.cmpb.2022.106654_bib0010) 2004; 94 Ng (10.1016/j.cmpb.2022.106654_bib0025) 2013; 13 10.1016/j.cmpb.2022.106654_bib0032 Hayes (10.1016/j.cmpb.2022.106654_bib0017) 2017 Bates (10.1016/j.cmpb.2022.106654_bib0030) 2015; 67 Brightwell (10.1016/j.cmpb.2022.106654_bib0027) 2013 Li (10.1016/j.cmpb.2022.106654_bib0008) 2015; 15 10.1016/j.cmpb.2022.106654_bib0018 Beasley (10.1016/j.cmpb.2022.106654_bib0031) 2004; 53 Lorenz (10.1016/j.cmpb.2022.106654_bib0001) 2018; 115 10.1016/j.cmpb.2022.106654_bib0015 Tekwe (10.1016/j.cmpb.2022.106654_bib0004) 2020; 54 Ma (10.1016/j.cmpb.2022.106654_bib0033) 2009; 9 Flynn (10.1016/j.cmpb.2022.106654_bib0023) 2004; 4 Davison (10.1016/j.cmpb.2022.106654_bib0024) 1997 10.1016/j.cmpb.2022.106654_bib0009 Leyrat (10.1016/j.cmpb.2022.106654_bib0013) 2017; 47 Aceves-Martins (10.1016/j.cmpb.2022.106654_bib0020) 2017; 13 Li (10.1016/j.cmpb.2022.106654_bib0016) 2021; 30 Murray (10.1016/j.cmpb.2022.106654_bib0007) 1998 Kahan (10.1016/j.cmpb.2022.106654_bib0002) 2016; 17 Golzarri-Arroyo (10.1016/j.cmpb.2022.106654_bib0005) 2020; 179 Brown (10.1016/j.cmpb.2022.106654_bib0011) 2015; 102 10.1016/j.cmpb.2022.106654_bib0028 Donner (10.1016/j.cmpb.2022.106654_bib0003) 2004; 94 10.1016/j.cmpb.2022.106654_bib0022 Campbell (10.1016/j.cmpb.2022.106654_bib0019) 2007; 26 Halekoh (10.1016/j.cmpb.2022.106654_bib0029) 2014; 59 McNeish (10.1016/j.cmpb.2022.106654_bib0014) 2016; 51 Huang (10.1016/j.cmpb.2022.106654_bib0026) 2018; 78 Campbell (10.1016/j.cmpb.2022.106654_bib0012) 2014 Aceves-Martins (10.1016/j.cmpb.2022.106654_bib0021) 2017; 13 Turner (10.1016/j.cmpb.2022.106654_bib0034) 2001; 20 Golzarri-Arroyo (10.1016/j.cmpb.2022.106654_bib0006) 2020; 16 |
| References_xml | – volume: 94 start-page: 416 year: 2004 end-page: 422 ident: bib0003 article-title: Pitfalls of and controversies in cluster randomization trials publication-title: Am. J. Public Health – year: 2017 ident: bib0017 article-title: Cluster Randomised Trials – reference: Health, N.I.o. – year: 1997 ident: bib0024 article-title: Bootstrap Methods and their Application – volume: 67 start-page: 48 year: 2015 ident: bib0030 article-title: Fitting Linear Mixed-Effects Models Usinglme4 publication-title: J. Stat. Soft. – volume: 9 start-page: 37 year: 2009 ident: bib0033 article-title: Comparison of Bayesian and classical methods in the analysis of cluster randomized controlled trials with a binary outcome: the community hypertension assessment trial (CHAT) publication-title: BMC Med. Res. Methodol. – reference: . 4/14/2021 [cited 2021 May 4th]; Available from: – year: 2014 ident: bib0012 article-title: How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research – volume: 51 start-page: 495 year: 2016 end-page: 518 ident: bib0014 article-title: Modeling clustered data with very few clusters publication-title: Multivar. Behav. Res. – volume: 59 start-page: 32 year: 2014 ident: bib0029 article-title: A Kenward-Roger approximation and parametric bootstrap methods for tests in linear mixed models - therpackagepbkrtest publication-title: J. Stat. Soft. – year: 1998 ident: bib0007 article-title: Design and Analysis of Group-Randomized Trials – volume: 16 start-page: 65 year: 2020 end-page: 66 ident: bib0006 article-title: Incorrect analyses of cluster-randomized trials that do not take clustering and nesting into account likely lead to p-values that are too small publication-title: Child Obes. – volume: 30 start-page: 612 year: 2021 end-page: 639 ident: bib0016 article-title: Mixed-effects models for the design and analysis of stepped wedge cluster randomized trials: An overview publication-title: Stat. Methods Med. Res. – volume: 15 start-page: 38 year: 2015 ident: bib0008 article-title: Comparing denominator degrees of freedom approximations for the generalized linear mixed model in analyzing binary outcome in small sample cluster-randomized trials publication-title: BMC Med. Res. Methodol – volume: 47 start-page: 321 year: 2017 end-page: 331 ident: bib0013 article-title: Cluster randomized trials with a small number of clusters: which analyses should be used? publication-title: Int. J. Epidemiol. – volume: 20 start-page: 453 year: 2001 end-page: 472 ident: bib0034 article-title: Bayesian methods of analysis for cluster randomized trials with binary outcome data publication-title: Stat. Med. – reference: . [cited 2020; Available from: – volume: 53 start-page: 95 year: 2004 end-page: 108 ident: bib0031 article-title: Chebyshev's inequality for nonparametric testing with small n and α in microarray research publication-title: J. Royal Stat. Soc. Series C (Applied Statistics) – volume: 17 start-page: 438 year: 2016 ident: bib0002 article-title: Increased risk of type I errors in cluster randomised trials with small or medium numbers of clusters: a review, reanalysis, and simulation study publication-title: Trials – volume: 4 start-page: 33 year: 2004 ident: bib0023 article-title: Use of the bootstrap in analysing cost data from cluster randomised trials: some simulation results publication-title: BMC Health Serv. Res. – volume: 13 start-page: 141 year: 2013 end-page: 164 ident: bib0025 article-title: Two-stage nonparametric bootstrap sampling with shrinkage correction for clustered data publication-title: The Stata J. – year: 2013 ident: bib0027 article-title: Avoid and Detect Statistical Malpractice: Design and Analysis for Biologists, with R – reference: (1468-4357 (Electronic)). – volume: 179 start-page: 1487 year: 2020 end-page: 1488 ident: bib0005 article-title: Incorrect design and analysis render conclusion unsubstantiated: comment on "A digital movement in the world of inactive children: favourable outcomes of playing active video games in a pilot randomized trial" publication-title: Eur. J. Pediatr. – volume: 13 start-page: 300 year: 2017 end-page: 313 ident: bib0021 article-title: Retracted: a school-based, peer-led, social marketing intervention to engage spanish adolescents in a healthy lifestyle (“we are cool”—som la pera study): a parallel-cluster randomized controlled study publication-title: Childhood Obes. – volume: 54 start-page: 139 year: 2020 ident: bib0004 article-title: Randomization by cluster, but analysis by individual without accommodating clustering in the analysis is incorrect: comment publication-title: Ann. Behav. Med. – reference: (0277-6715 (Print)). – reference: 2007. 69(3): p. 369-390. – reference: Murray, D.M., et al., – reference: Field, C.A. and A.H. Welsh, – reference: . – volume: 115 start-page: 163 year: 2018 end-page: 168 ident: bib0001 article-title: Cluster-Randomized Studies publication-title: Dtsch Arztebl Int. – volume: 94 start-page: 423 year: 2004 end-page: 432 ident: bib0010 article-title: Design and analysis of group-randomized trials: a review of recent methodological developments publication-title: Am. J. Public Health – volume: 13 start-page: 300 year: 2017 end-page: 313 ident: bib0020 article-title: A school-based, peer-led, social marketing intervention to engage spanish adolescents in a healthy lifestyle ("we are cool"-som la pera study): a parallel-cluster randomized controlled study publication-title: Child Obes – reference: Li, F., et al., – reference: 2017. 358: p. j3064. – volume: 78 start-page: 297 year: 2018 end-page: 318 ident: bib0026 article-title: Using cluster bootstrapping to analyze nested data with a few clusters publication-title: Educ. Psychol. Meas. – volume: 102 start-page: 241 year: 2015 end-page: 248 ident: bib0011 article-title: Best (but oft-forgotten) practices: designing, analyzing, and reporting cluster randomized controlled trials publication-title: Am. J. Clin. Nutr. – volume: 26 start-page: 2 year: 2007 end-page: 19 ident: bib0019 article-title: Developments in cluster randomized trials and Statistics in Medicine publication-title: Stat. Med. – reference: Science, P.S.E.C.o. – reference: Hemming, K., et al., – ident: 10.1016/j.cmpb.2022.106654_bib0028 – year: 1997 ident: 10.1016/j.cmpb.2022.106654_bib0024 – volume: 179 start-page: 1487 issue: 9 year: 2020 ident: 10.1016/j.cmpb.2022.106654_bib0005 article-title: Incorrect design and analysis render conclusion unsubstantiated: comment on "A digital movement in the world of inactive children: favourable outcomes of playing active video games in a pilot randomized trial" publication-title: Eur. J. Pediatr. doi: 10.1007/s00431-020-03590-y – volume: 9 start-page: 37 issue: 1 year: 2009 ident: 10.1016/j.cmpb.2022.106654_bib0033 article-title: Comparison of Bayesian and classical methods in the analysis of cluster randomized controlled trials with a binary outcome: the community hypertension assessment trial (CHAT) publication-title: BMC Med. Res. Methodol. doi: 10.1186/1471-2288-9-37 – volume: 94 start-page: 423 issue: 3 year: 2004 ident: 10.1016/j.cmpb.2022.106654_bib0010 article-title: Design and analysis of group-randomized trials: a review of recent methodological developments publication-title: Am. J. Public Health doi: 10.2105/AJPH.94.3.423 – volume: 102 start-page: 241 issue: 2 year: 2015 ident: 10.1016/j.cmpb.2022.106654_bib0011 article-title: Best (but oft-forgotten) practices: designing, analyzing, and reporting cluster randomized controlled trials publication-title: Am. J. Clin. Nutr. doi: 10.3945/ajcn.114.105072 – volume: 4 start-page: 33 issue: 1 year: 2004 ident: 10.1016/j.cmpb.2022.106654_bib0023 article-title: Use of the bootstrap in analysing cost data from cluster randomised trials: some simulation results publication-title: BMC Health Serv. Res. doi: 10.1186/1472-6963-4-33 – ident: 10.1016/j.cmpb.2022.106654_bib0009 doi: 10.1136/bmj.j3064 – ident: 10.1016/j.cmpb.2022.106654_bib0018 – year: 2014 ident: 10.1016/j.cmpb.2022.106654_bib0012 – ident: 10.1016/j.cmpb.2022.106654_bib0015 – ident: 10.1016/j.cmpb.2022.106654_bib0032 – year: 2017 ident: 10.1016/j.cmpb.2022.106654_bib0017 – volume: 115 start-page: 163 issue: 10 year: 2018 ident: 10.1016/j.cmpb.2022.106654_bib0001 article-title: Cluster-Randomized Studies publication-title: Dtsch Arztebl Int. – volume: 94 start-page: 416 issue: 3 year: 2004 ident: 10.1016/j.cmpb.2022.106654_bib0003 article-title: Pitfalls of and controversies in cluster randomization trials publication-title: Am. J. Public Health doi: 10.2105/AJPH.94.3.416 – volume: 51 start-page: 495 issue: 4 year: 2016 ident: 10.1016/j.cmpb.2022.106654_bib0014 article-title: Modeling clustered data with very few clusters publication-title: Multivar. Behav. Res. doi: 10.1080/00273171.2016.1167008 – volume: 16 start-page: 65 issue: 2 year: 2020 ident: 10.1016/j.cmpb.2022.106654_bib0006 article-title: Incorrect analyses of cluster-randomized trials that do not take clustering and nesting into account likely lead to p-values that are too small publication-title: Child Obes. doi: 10.1089/chi.2019.0142 – year: 2013 ident: 10.1016/j.cmpb.2022.106654_bib0027 – volume: 13 start-page: 300 issue: 4 year: 2017 ident: 10.1016/j.cmpb.2022.106654_bib0020 article-title: A school-based, peer-led, social marketing intervention to engage spanish adolescents in a healthy lifestyle ("we are cool"-som la pera study): a parallel-cluster randomized controlled study publication-title: Child Obes doi: 10.1089/chi.2016.0216 – ident: 10.1016/j.cmpb.2022.106654_bib0022 doi: 10.1111/j.1467-9868.2007.00593.x – volume: 47 start-page: 321 issue: 1 year: 2017 ident: 10.1016/j.cmpb.2022.106654_bib0013 article-title: Cluster randomized trials with a small number of clusters: which analyses should be used? publication-title: Int. J. Epidemiol. doi: 10.1093/ije/dyx169 – volume: 15 start-page: 38 issue: 1 year: 2015 ident: 10.1016/j.cmpb.2022.106654_bib0008 article-title: Comparing denominator degrees of freedom approximations for the generalized linear mixed model in analyzing binary outcome in small sample cluster-randomized trials publication-title: BMC Med. Res. Methodol doi: 10.1186/s12874-015-0026-x – volume: 20 start-page: 453 issue: 3 year: 2001 ident: 10.1016/j.cmpb.2022.106654_bib0034 article-title: Bayesian methods of analysis for cluster randomized trials with binary outcome data publication-title: Stat. Med. doi: 10.1002/1097-0258(20010215)20:3<453::AID-SIM803>3.0.CO;2-L – volume: 30 start-page: 612 issue: 2 year: 2021 ident: 10.1016/j.cmpb.2022.106654_bib0016 article-title: Mixed-effects models for the design and analysis of stepped wedge cluster randomized trials: An overview publication-title: Stat. Methods Med. Res. doi: 10.1177/0962280220932962 – volume: 78 start-page: 297 issue: 2 year: 2018 ident: 10.1016/j.cmpb.2022.106654_bib0026 article-title: Using cluster bootstrapping to analyze nested data with a few clusters publication-title: Educ. Psychol. Meas. doi: 10.1177/0013164416678980 – volume: 53 start-page: 95 issue: 1 year: 2004 ident: 10.1016/j.cmpb.2022.106654_bib0031 article-title: Chebyshev's inequality for nonparametric testing with small n and α in microarray research publication-title: J. Royal Stat. Soc. Series C (Applied Statistics) doi: 10.1111/j.1467-9876.2004.00428.x – volume: 54 start-page: 139 issue: 2 year: 2020 ident: 10.1016/j.cmpb.2022.106654_bib0004 article-title: Randomization by cluster, but analysis by individual without accommodating clustering in the analysis is incorrect: comment publication-title: Ann. Behav. Med. doi: 10.1093/abm/kaz065 – volume: 13 start-page: 141 issue: 1 year: 2013 ident: 10.1016/j.cmpb.2022.106654_bib0025 article-title: Two-stage nonparametric bootstrap sampling with shrinkage correction for clustered data publication-title: The Stata J. doi: 10.1177/1536867X1301300111 – volume: 17 start-page: 438 issue: 1 year: 2016 ident: 10.1016/j.cmpb.2022.106654_bib0002 article-title: Increased risk of type I errors in cluster randomised trials with small or medium numbers of clusters: a review, reanalysis, and simulation study publication-title: Trials doi: 10.1186/s13063-016-1571-2 – volume: 59 start-page: 32 issue: 9 year: 2014 ident: 10.1016/j.cmpb.2022.106654_bib0029 article-title: A Kenward-Roger approximation and parametric bootstrap methods for tests in linear mixed models - therpackagepbkrtest publication-title: J. Stat. Soft. doi: 10.18637/jss.v059.i09 – volume: 67 start-page: 48 issue: 1 year: 2015 ident: 10.1016/j.cmpb.2022.106654_bib0030 article-title: Fitting Linear Mixed-Effects Models Usinglme4 publication-title: J. Stat. Soft. doi: 10.18637/jss.v067.i01 – volume: 26 start-page: 2 issue: 1 year: 2007 ident: 10.1016/j.cmpb.2022.106654_bib0019 article-title: Developments in cluster randomized trials and Statistics in Medicine publication-title: Stat. Med. doi: 10.1002/sim.2731 – year: 1998 ident: 10.1016/j.cmpb.2022.106654_bib0007 – volume: 13 start-page: 300 issue: 4 year: 2017 ident: 10.1016/j.cmpb.2022.106654_bib0021 article-title: Retracted: a school-based, peer-led, social marketing intervention to engage spanish adolescents in a healthy lifestyle (“we are cool”—som la pera study): a parallel-cluster randomized controlled study publication-title: Childhood Obes. doi: 10.1089/chi.2016.0216 |
| SSID | ssj0002556 |
| Score | 2.3534565 |
| Snippet | •The type I error rate is inflated under scenarios of a small number of clusters per treatment in a cluster randomized trials when using parametric... Cluster randomized controlled trials (cRCTs) are increasingly used but must be analyzed carefully. We conducted a simulation study to evaluate the validity of... |
| SourceID | pubmedcentral proquest pubmed crossref elsevier |
| SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 106654 |
| SubjectTerms | Cluster Analysis Computer Simulation Humans Linear Models Research Design Sample Size |
| Title | Evaluation of the type I error rate when using parametric bootstrap analysis of a cluster randomized controlled trial with binary outcomes and a small number of clusters |
| URI | https://www.clinicalkey.com/#!/content/1-s2.0-S0169260722000396 https://dx.doi.org/10.1016/j.cmpb.2022.106654 https://www.ncbi.nlm.nih.gov/pubmed/35093646 https://www.proquest.com/docview/2624201471 https://pubmed.ncbi.nlm.nih.gov/PMC8847311 |
| Volume | 215 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwELaqIiEuiDdLoRokbihsnDivY1W12oLaC1TqLbInNl20m6x2s0Li0P_Dv2QmcQILokjc8vBYVmZif2PPfCPEm9g65SSaAE1ODgqB0kBnWARos0jbyjkZczby-UU6u1Tvr5KrPXE85MJwWKWf-_s5vZut_ZOp_5rT1Xw-_cg8IoTGsyjqMkyZdlupjK383c3PMA-m2Or5vYuAW_vEmT7GC5crQz5iFNEDLsP7t8XpT_D5ewzlL4vS6QNx36NJOOoH_FDs2fqRuHvuz8sfi-8nI5k3NA4I7AHvucIZ2PW6WQPzRMDXa1sDx79_BiYCX3KNLQRC3y1vg6xAe94S7kEDLrbMrUCiddUs599sBT7cfUGXXREQ4M1dMF2mLzTblr6t3VA3FYlvlnqxgL4OCXfou9s8EZenJ5-OZ4EvzhBgEqZtkOeVcUjeWkIQIVHa6Yw8p4z0HpsqrawOUVkXFqgI8jhSO0qLiY4wNYVB7eKnYr9uavtcAFYY64jWUFS5kmGhjQkjl8tEY5ZWMp8IOWilRM9czgU0FuUQovalZE2WrMmy1-REvB1lVj1vx62t40HZ5ZCRSnNoScvKrVLJKLVjs_-Uez3YU0k_M5_Q6No2200ZcbYOOa2ZnIhnvX2No48J2sWpSici27G8sQEThe--qefXHWF4ThAklvLFf473QNzjuz7y7qXYb9db-4qgWGsOu3_tUNw5Ovswu_gBzqg5Pw |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3da9swEBddCttexr6XfWqwt2Fi-duPpbQka5OXtdA3IZ2lNcOxQ-JQ6H-0_3J3tmyWjXWwNyP7hPBJp99Jd79j7FNobGQFaA90hg4KglJPpZB7YNJAmcJaEVI28nyRTC-jL1fx1QE77nNhKKzS2f7OprfW2rVM3N-crJfLyVfiEUE0ngZBm2Ga3GOHxE4Vj9jh0exsuhgMMrFsdRTfuUcCLnemC_OC1VqjmxgE2ECVeP-2P_2JP38Po_xlXzp9zB45QMmPujE_YQemesruz92V-TP242Tg8-a15Yj3OB278hk3m0294UQVwW-uTcUpBP4bJy7wFZXZAo4AvKGTkDVXjrqEelAcyh3RK6BoVdSr5a0puIt4L_GxrQPC6XyX6zbZl9e7Bn-v2WI3BYpvV6oseVeKhDp03W2fs8vTk4vjqefqM3gQ-0njZVmhLaDDFiNKiCNlVYrOU4qqD3WRFEb5EBnr5xAh6rGoeRAGYhVAonMNyoYv2KiqK_OKcSggVAFuoxBlkfBzpbUf2EzECtKkENmYiV4rEhx5OdXQKGUfpfZdkiYlaVJ2mhyzz4PMuqPuuPPrsFe27JNS0YxK3FnulIoHqb1p-0-5j_18krie6ZJGVabebWVACTvot6ZizF5282sYfYjoLkyiZMzSvZk3fEBc4ftvquV1yxmeIQoJhXj9n-P9wB5ML-bn8ny2OHvDHtKbLhDvLRs1m515h8is0e_dyvsJX4E78A |
| 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=Evaluation+of+the+type+I+error+rate+when+using+parametric+bootstrap+analysis+of+a+cluster+randomized+controlled+trial+with+binary+outcomes+and+a+small+number+of+clusters&rft.jtitle=Computer+methods+and+programs+in+biomedicine&rft.au=Golzarri-Arroyo%2C+Lilian&rft.au=Dickinson%2C+Stephanie+L.&rft.au=Jamshidi-Naeini%2C+Yasaman&rft.au=Zoh%2C+Roger+S.&rft.date=2022-03-01&rft.pub=Elsevier+B.V&rft.issn=0169-2607&rft.volume=215&rft_id=info:doi/10.1016%2Fj.cmpb.2022.106654&rft.externalDocID=S0169260722000396 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0169-2607&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0169-2607&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0169-2607&client=summon |