Carrying out streamlined routine data analyses with reports for observational studies: introduction to a series of generic SAS ® macros [version 2; peer review: 2 approved]
For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw valid conclusions. However, generating reports in SAS ® for routine analyses can be a time-consuming and tedious process, especially when de...
Saved in:
| Published in | F1000 research Vol. 7; p. 1955 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Faculty of 1000 Ltd
2018
F1000 Research Limited F1000 Research Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2046-1402 2046-1402 |
| DOI | 10.12688/f1000research.16866.2 |
Cover
| Abstract | For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw valid conclusions. However, generating reports in SAS
® for routine analyses can be a time-consuming and tedious process, especially when dealing with large databases with a massive number of variables in an iterative and collaborative research environment. In this work, we present a general workflow of research based on an observational database and a series of SAS
® macros that fits this framework, which covers a streamlined data analyses and produces journal-quality summary tables. The system is generic enough to fit a variety of research projects and enables researchers to build a highly organized and concise coding for quick updates as research evolves. The result reports promote communication in collaborations and will escort the research with ease and efficiency. |
|---|---|
| AbstractList | For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw valid conclusions. However, generating reports in SAS® for routine analyses can be a time-consuming and tedious process, especially when dealing with large databases with a massive number of variables in an iterative and collaborative research environment. In this work, we present a general workflow of research based on an observational database and a series of SAS® macros that fits this framework, which covers a streamlined data analyses and produces journal-quality summary tables. The system is generic enough to fit a variety of research projects and enables researchers to build a highly organized and concise coding for quick updates as research evolves. The result reports promote communication in collaborations and will escort the research with ease and efficiency. For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw valid conclusions. However, generating reports in SAS ® for routine analyses can be a time-consuming and tedious process, especially when dealing with large databases with a massive number of variables in an iterative and collaborative research environment. In this work, we present a general workflow of research based on an observational database and a series of SAS ® macros that fits this framework, which covers a streamlined data analyses and produces journal-quality summary tables. The system is generic enough to fit a variety of research projects and enables researchers to build a highly organized and concise coding for quick updates as research evolves. The result reports promote communication in collaborations and will escort the research with ease and efficiency. For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw valid conclusions. However, generating reports in SAS ® for routine analyses can be a time-consuming and tedious process, especially when dealing with large databases with a massive number of variables in an iterative and collaborative research environment. In this work, we present a general workflow of research based on an observational database and a series of SAS ® macros that fits this framework, which covers a streamlined data analyses and produces journal-quality summary tables. The system is generic enough to fit a variety of research projects and enables researchers to build a highly organized and concise coding for quick updates as research evolves. The result reports promote communication in collaborations and will escort the research with ease and efficiency. For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw valid conclusions. However, generating reports in SAS ® for routine analyses can be a time-consuming and tedious process, especially when dealing with large databases with a massive number of variables in an iterative and collaborative research environment. In this work, we present a general workflow of research based on an observational database and a series of SAS ® macros that fits this framework, which covers a streamlined data analyses and produces journal-quality summary tables. The system is generic enough to fit a variety of research projects and enables researchers to build a highly organized and concise coding for quick updates as research evolves. The result reports promote communication in collaborations and will escort the research with ease and efficiency. For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw valid conclusions. However, generating reports in SAS for routine analyses can be a time-consuming and tedious process, especially when dealing with large databases with a massive number of variables in an iterative and collaborative research environment. In this work, we present a general workflow of research based on an observational database and a series of SAS macros that fits this framework, which covers a streamlined data analyses and produces journal-quality summary tables. The system is generic enough to fit a variety of research projects and enables researchers to build a highly organized and concise coding for quick updates as research evolves. The result reports promote communication in collaborations and will escort the research with ease and efficiency. For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw valid conclusions. However, generating reports in SAS ® for routine analyses can be a time-consuming and tedious process, especially when dealing with large databases with a massive number of variables in an iterative and collaborative research environment. In this work, we present a general workflow of research based on an observational database and a series of SAS ® macros that fits this framework, which covers a streamlined data analyses and produces journal-quality summary tables. The system is generic enough to fit a variety of research projects and enables researchers to build a highly organized and concise coding for quick updates as research evolves. The result reports promote communication in collaborations and will escort the research with ease and efficiency.For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw valid conclusions. However, generating reports in SAS ® for routine analyses can be a time-consuming and tedious process, especially when dealing with large databases with a massive number of variables in an iterative and collaborative research environment. In this work, we present a general workflow of research based on an observational database and a series of SAS ® macros that fits this framework, which covers a streamlined data analyses and produces journal-quality summary tables. The system is generic enough to fit a variety of research projects and enables researchers to build a highly organized and concise coding for quick updates as research evolves. The result reports promote communication in collaborations and will escort the research with ease and efficiency. |
| Author | Liu, Yuan Nickleach, Dana C Kowalski, Jeanne Zhang, Chao Switchenko, Jeffrey M |
| Author_xml | – sequence: 1 givenname: Yuan orcidid: 0000-0001-8926-3058 surname: Liu fullname: Liu, Yuan email: yliu31@emory.edu organization: Biostatistics and Bioinformatics Shared Resource, Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA – sequence: 2 givenname: Dana C surname: Nickleach fullname: Nickleach, Dana C organization: Biostatistics and Bioinformatics Shared Resource, Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA – sequence: 3 givenname: Chao orcidid: 0000-0002-9066-8658 surname: Zhang fullname: Zhang, Chao organization: Biostatistics and Bioinformatics Shared Resource, Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA – sequence: 4 givenname: Jeffrey M surname: Switchenko fullname: Switchenko, Jeffrey M organization: Biostatistics and Bioinformatics Shared Resource, Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA – sequence: 5 givenname: Jeanne surname: Kowalski fullname: Kowalski, Jeanne organization: Department of Oncology, University of Texas, Austin, Texas, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31231506$$D View this record in MEDLINE/PubMed |
| BookMark | eNqFks9uEzEQxleoiJbSV6gsceGSYM96vbsBVaoi_lSqxKFwQsia9c4mjjbrYO-mykPBQ_BkOEkLTQ9w8mj8-z6PPN_z5KhzHSXJueBjAaooXjeCc-4pEHozHwtVKDWGJ8kJcKlGQnI4elAfJ2chLKKAl2WqIH-WHKcCUpFxdZL8mKL3G9vNmBt6FnpPuGxtRzXzsRELVmOPDDtsN4ECu7X9nHlaOd8H1jjPXBXIr7G3LiLRYKgthQmzXe9dPZhtn_WOIYtYvGGuYTPqYm3YzeUN-_WTLdF4F9jXNfmwpeENWxH5-Mra0u2EAcPVyrs11d9eJE8bbAOd3Z2nyZf37z5PP46uP324ml5ej4zMJYxESSDqRjZQFlBKTLlSOZS5rLMKgIsi51UjZSZNxkvMq1pUmSlyQN5kiiSlp8nV3rd2uNArb5foN9qh1buG8zONvremJQ2mSJXMlMISpQBRibyuUpBVmVUKZBG9LvZeq6FaUm0o_gy2B6aHN52d65lba5VthxbR4NWdgXffBwq9XtpgqG2xIzcEnYoCiiKPbERfPkIXbvBxMUEDyDLmJCYlUucPJ_ozyn0qIvB2D2wXEzw12th-t-I4oG214HqXQ32QQ73LoYYoV4_k9y_8VzjZCxs0Q9tvtpD-S_1b_Bs63fly |
| CitedBy_id | crossref_primary_10_1097_COC_0000000000001125 crossref_primary_10_3389_fonc_2022_1074675 crossref_primary_10_1136_jitc_2023_007235 crossref_primary_10_1245_s10434_020_09279_8 crossref_primary_10_1002_hed_27282 crossref_primary_10_1002_jso_25976 crossref_primary_10_1634_theoncologist_2019_0661 crossref_primary_10_1002_jso_27814 crossref_primary_10_1002_jso_27503 crossref_primary_10_1200_OP_22_00781 crossref_primary_10_3389_fonc_2021_728076 crossref_primary_10_1097_COC_0000000000001093 crossref_primary_10_1007_s00404_024_07421_5 crossref_primary_10_1016_j_clgc_2021_03_007 crossref_primary_10_1002_cam4_70624 crossref_primary_10_1002_cncr_33660 |
| Cites_doi | 10.1046/j.1524-4733.2003.00242.x 10.1016/j.jtho.2015.10.007 10.1377/hlthaff.2010.0666 10.21037/atm.2018.08.13 10.1002/sim.6265 10.1080/01621459.1999.10474144 10.1002/cpt.320 10.1111/j.1524-4733.2009.00602.x 10.1111/j.1524-4733.2009.00600.x 10.1245/s10434-007-9747-3 10.1111/j.1524-4733.2009.00601.x 10.2471/BLT.07.045120 10.1080/00273171.2011.568786 10.1056/NEJMsr077003 |
| ContentType | Journal Article |
| Copyright | Copyright: © 2019 Liu Y et al. Copyright: © 2019 Liu Y et al. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Copyright: © 2019 Liu Y et al. 2019 |
| Copyright_xml | – notice: Copyright: © 2019 Liu Y et al. – notice: Copyright: © 2019 Liu Y et al. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: Copyright: © 2019 Liu Y et al. 2019 |
| DBID | C-E CH4 AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7X7 7XB 88I 8FE 8FH 8FI 8FJ 8FK ABUWG AFKRA AZQEC BBNVY BENPR BHPHI CCPQU DWQXO FYUFA GHDGH GNUQQ HCIFZ K9. LK8 M0S M2P M7P PHGZM PHGZT PIMPY PKEHL PQEST PQGLB PQQKQ PQUKI PRINS Q9U 7X8 5PM DOA |
| DOI | 10.12688/f1000research.16866.2 |
| DatabaseName | F1000Research Faculty of 1000 CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) ProQuest Health & Medical Collection ProQuest Central (purchase pre-March 2016) Science Database (Alumni Edition) ProQuest SciTech Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials - QC Biological Science Collection ProQuest Central Natural Science Collection ProQuest One Community College ProQuest Central Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Biological Sciences ProQuest Health & Medical Collection Science Database ProQuest Biological Science ProQuest Central Premium ProQuest One Academic (New) ProQuest Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Publicly Available Content Database ProQuest Central Student ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Natural Science Collection ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Biological Science Collection ProQuest Central (New) ProQuest Science Journals (Alumni Edition) ProQuest Biological Science Collection ProQuest Central Basic ProQuest Science Journals ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | CrossRef Publicly Available Content Database MEDLINE MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 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: 3 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 4 dbid: BENPR name: ProQuest Central url: http://www.proquest.com/pqcentral?accountid=15518 sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine Women's Studies |
| EISSN | 2046-1402 |
| ExternalDocumentID | oai_doaj_org_article_2c8364566a9a4121b17db324b95b6248 PMC6567291 31231506 10_12688_f1000research_16866_2 |
| Genre | Research Support, Non-U.S. Gov't Journal Article Research Support, N.I.H., Extramural |
| GeographicLocations | Atlanta Georgia United States--US |
| GeographicLocations_xml | – name: Atlanta Georgia – name: United States--US |
| GrantInformation_xml | – fundername: Winship Cancer Institute grantid: P30CA138292 – fundername: NCI NIH HHS grantid: P30 CA138292 |
| GroupedDBID | 3V. 53G 5VS 7X7 88I 8FE 8FH 8FI 8FJ ABUWG ACGOD ACPRK ADACO ADBBV ADRAZ AFKRA AHMBA ALMA_UNASSIGNED_HOLDINGS AZQEC BAWUL BBAFP BBNVY BCNDV BENPR BHPHI BPHCQ BVXVI C-E CH4 DIK DWQXO FRP FYUFA GNUQQ GROUPED_DOAJ GX1 HCIFZ HYE KQ8 LK8 M2P M7P OK1 PIMPY PQEST PQQKQ PQUKI PRINS PROAC RPM AAFWJ AAYXX AFPKN ALIPV AOIJS CCPQU CITATION HMCUK M48 M~E PGMZT PHGZM PHGZT UKHRP W2D CGR CUY CVF ECM EIF NPM PQGLB 7XB 8FK K9. PKEHL Q9U 7X8 PUEGO 5PM |
| ID | FETCH-LOGICAL-c4742-19e21df4f298294a306672974d5b2201870bf4454c509a7bd1b5c872a0f56e4e3 |
| IEDL.DBID | M48 |
| ISSN | 2046-1402 |
| IngestDate | Wed Aug 27 01:26:08 EDT 2025 Thu Aug 21 18:41:35 EDT 2025 Fri Sep 05 17:47:54 EDT 2025 Fri Jul 25 12:06:50 EDT 2025 Mon Jul 21 05:57:20 EDT 2025 Tue Jul 01 04:27:04 EDT 2025 Thu Apr 24 23:01:00 EDT 2025 Mon Jan 18 12:18:50 EST 2021 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | SAS® macros observational studies collaborative reporting streamlined data process Good-Research-Practice |
| Language | English |
| License | http://creativecommons.org/licenses/by/4.0/: This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c4742-19e21df4f298294a306672974d5b2201870bf4454c509a7bd1b5c872a0f56e4e3 |
| Notes | new_version ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 No competing interests were disclosed. |
| ORCID | 0000-0001-8926-3058 0000-0002-9066-8658 |
| OpenAccessLink | http://journals.scholarsportal.info/openUrl.xqy?doi=10.12688/f1000research.16866.2 |
| PMID | 31231506 |
| PQID | 2249686866 |
| PQPubID | 2045578 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_2c8364566a9a4121b17db324b95b6248 pubmedcentral_primary_oai_pubmedcentral_nih_gov_6567291 proquest_miscellaneous_3182887729 proquest_journals_2249686866 pubmed_primary_31231506 crossref_citationtrail_10_12688_f1000research_16866_2 crossref_primary_10_12688_f1000research_16866_2 faculty1000_research_10_12688_f1000research_16866_2 |
| ProviderPackageCode | C-E CH4 CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2018-00-00 |
| PublicationDateYYYYMMDD | 2018-01-01 |
| PublicationDate_xml | – year: 2018 text: 2018-00-00 |
| PublicationDecade | 2010 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England – name: London – name: London, UK |
| PublicationTitle | F1000 research |
| PublicationTitleAlternate | F1000Res |
| PublicationYear | 2018 |
| Publisher | Faculty of 1000 Ltd F1000 Research Limited F1000 Research Ltd |
| Publisher_xml | – name: Faculty of 1000 Ltd – name: F1000 Research Limited – name: F1000 Research Ltd |
| References | J Fine (ref-21) 1999; 94 E von Elm (ref-7) 2007; 85 B Motheral (ref-11) 2003; 6 R Ball (ref-3) 2016; 99 Y Liu (ref-13) 2018 P Austin (ref-14) 2011; 46 H Gu (ref-16) 2018; 6 E Frank (ref-15) 2006 N Dreyer (ref-5) 2010; 29 L Hansen (ref-4) 2011 L Zhao (ref-18) 2005 E Cox (ref-9) 2009; 12 N Dreyer (ref-6) 2010; 16 M Berger (ref-10) 2009; 12 B Hankey (ref-1) 1999; 8 M Johnson (ref-8) 2009; 12 W Sauerbrei (ref-12) 2014; 33 G Grandits (ref-17) 2006 R Wang (ref-22) 2007; 357 K Bilimoria (ref-2) 2008; 15 R Medbery (ref-20) 2016; 11 D Nickleach (ref-19) |
| References_xml | – volume: 16 start-page: 467-471 year: 2010 ident: ref-6 article-title: GRACE principles: recognizing high-quality observational studies of comparative effectiveness. publication-title: Am J Manag Care. – year: 2006 ident: ref-15 article-title: Regression Modeling Strategies – volume: 6 start-page: 90-97 year: 2003 ident: ref-11 article-title: A checklist for retrospective database studies--report of the ISPOR Task Force on Retrospective Databases. publication-title: Value Health. doi: 10.1046/j.1524-4733.2003.00242.x – volume: 11 start-page: 222-233 year: 2016 ident: ref-20 article-title: Nodal Upstaging Is More Common with Thoracotomy than with VATS During Lobectomy for Early-Stage Lung Cancer: An Analysis from the National Cancer Data Base. publication-title: J Thorac Oncol. doi: 10.1016/j.jtho.2015.10.007 – volume: 29 start-page: 1818-1825 year: 2010 ident: ref-5 article-title: Why observational studies should be among the tools used in comparative effectiveness research. publication-title: Health Aff (Millwood). doi: 10.1377/hlthaff.2010.0666 – volume: 6 start-page: 326 year: 2018 ident: ref-16 article-title: %ggBaseline: a SAS macro for analyzing and reporting baseline characteristics automatically in medical research. publication-title: Ann Transl Med. doi: 10.21037/atm.2018.08.13 – volume: 33 start-page: 5413-5432 year: 2014 ident: ref-12 article-title: STRengthening analytical thinking for observational studies: the STRATOS initiative. publication-title: Stat Med. doi: 10.1002/sim.6265 – volume: 94 start-page: 496-509 year: 1999 ident: ref-21 article-title: A Proportional Hazards Model for the Subdistribution of a Competing Risk. publication-title: J Am Stat Assoc. doi: 10.1080/01621459.1999.10474144 – volume: 99 start-page: 265-268 year: 2016 ident: ref-3 article-title: The FDA's sentinel initiative--A comprehensive approach to medical product surveillance. publication-title: Clin Pharmacol Ther. doi: 10.1002/cpt.320 – volume: 12 start-page: 1062-1073 year: 2009 ident: ref-8 article-title: Good research practices for comparative effectiveness research: analytic methods to improve causal inference from nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report--Part III. publication-title: Value Health. doi: 10.1111/j.1524-4733.2009.00602.x – year: 2018 ident: ref-13 article-title: Emory-Yuan/BBISR-SAS-Macros V1 (Version V1). publication-title: Zenodo. – volume: 12 start-page: 1044-1052 year: 2009 ident: ref-10 article-title: Good research practices for comparative effectiveness research: defining, reporting and interpreting nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report--Part I. publication-title: Value Health. doi: 10.1111/j.1524-4733.2009.00600.x – volume: 15 start-page: 683-690 year: 2008 ident: ref-2 article-title: The National Cancer Data Base: a powerful initiative to improve cancer care in the United States. publication-title: Ann Surg Oncol. doi: 10.1245/s10434-007-9747-3 – year: 2006 ident: ref-17 article-title: A System of SAS® Macros for Producing Statistical Reports – volume: 12 start-page: 1053-1061 year: 2009 ident: ref-9 article-title: Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report--Part II. publication-title: Value Health. doi: 10.1111/j.1524-4733.2009.00601.x – ident: ref-19 article-title: SAS® Macros to Conduct Common Biostatistical Analyses and Generate Reports. publication-title: SESUG 2013: The Proceeding of the SouthEast SAS User Group. – volume: 8 start-page: 1117-1121 year: 1999 ident: ref-1 article-title: The surveillance, epidemiology, and end results program: a national resource. publication-title: Cancer Epidemiol Biomarkers Prev. – year: 2011 ident: ref-4 article-title: Health Research Data for the Real World: The MarketScan Databases. publication-title: White Paper: TRUVEN Health Analytics. – volume: 85 start-page: 867-872 year: 2007 ident: ref-7 article-title: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. publication-title: Bull World Health Organ. doi: 10.2471/BLT.07.045120 – volume: 46 start-page: 399-424 year: 2011 ident: ref-14 article-title: An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies. publication-title: Multivariate Behav Res. doi: 10.1080/00273171.2011.568786 – year: 2005 ident: ref-18 article-title: A SAS® Macro for Producing Customized Reports – volume: 357 start-page: 2189-2194 year: 2007 ident: ref-22 article-title: Statistics in medicine--reporting of subgroup analyses in clinical trials. publication-title: N Engl J Med. doi: 10.1056/NEJMsr077003 |
| SSID | ssj0000993627 |
| Score | 2.341632 |
| Snippet | For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw... |
| SourceID | doaj pubmedcentral proquest pubmed crossref faculty1000 |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 1955 |
| SubjectTerms | Bias Bioinformatics Biomedical Research Cancer Data Analysis Data processing Databases, Factual Humans Hypotheses Literature reviews Medical research Observational studies Observational Studies as Topic - statistics & numerical data Population Researchers Software Software Tool Variables |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3da9UwFA-yB3EPQ-dXdcoRBJ-6tWn6NZ_mcAxhvszBQCQkaeLucO1o7x34P4l_hH-Z5yRdvVeE--JbadKkTU7PV875HcZeK2UUCh4RG250LESdxRoFdWxspgyKD2NrSnA--Vgcn4kP5_n5UqkvigkL8MBh4fa4qeikrChUrUTKU52WjUYtQNe5Lrjwab5JnSwZU5dB70HOTLnSHA3AOPVhPD49mBdo8jnyao9oOhe7aVEVxS5fkUwewH-TbTpFCBjfqf-_dNC_QymXZNPRfbY1KpVwED7mAbtj221292Q8Nt9mW75O5ZsBxqjBh-zHoep7ynCCbjEHShhRV6RwNtDjDbwACh0F5SFL7ADkroXxfAFQz4VOT-5cnHkI4-7DjALfm4BIC_MOFBCJ4wCdg6-EcD0zcHpw-usnXClaBvh8Exx2wN_CtbU9hFyafeDg4c5vbPPlETs7ev_p8DgeCzfERqCpHae15WnjhON1xWuhMoqk5Wi5NLnmnMoAJtoJkQuD6ooqdZPq3FQlV4nLCyts9phttF1rnzJwZVYlylYmMaVwyF5cYqqmMYaXuk4qF7H8dtOkGVHNqbjGN0nWDW22XNls6Tdb8ojtTc9dB1yPtU-8I5qYehMut7-B1CpHapXrqDVi2RJFyT9zrJl655by5MhiBom6V43N2CFir6ZmZA504qNa2y0GiQyboxTBtY_Yk0Co0_tnqLMQvGTEyhUSXvnA1ZZ2duEByNEGwCHTZ_9jRZ6ze0QRwau1wzbm_cK-QD1vrl_6X_o3_WdO5g priority: 102 providerName: Directory of Open Access Journals – databaseName: ProQuest Health & Medical Collection dbid: 7X7 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwhV3NbtQwEB5BkRA9VFD-AgUZCYlT2sRx4oQLKhVVhVQupdLeLNux25VoUpLdQ9-gT8ND8GTMJN60ixDVXlb5sZPMeObzePwNwHutrUbHI2LLrYmFqLLYoKOOrcu0RfdhXUUbnI-_FUen4ussn4WAWx_SKlc2cTDUdWspRr6HrqYqSvwVny5_xlQ1ilZXQwmN-_AgRSRCpRvkTE4xFkQ_aJ9l2BjMC5zseYpnBx6d892U2tvlaz5poO7fhE2vifviiq7_F_r8O4nyllc6fAxbAU6y_VH-T-Cea7bh4XFYMN-GraFC5YeehXzBp3B9oLuO9jaxdrlgtFVEXxDUrFmHB_APo6RRpgeyEtczCtSysLLAEOGy1kyBXOy5H9v9yOaU8l6PXLRs0TLNSLmxgdazM-K2nlt2sn_Cfv9iF5q-wzM4Pfzy_eAoDuUYYitwAh2nleNp7YXnVckroTPKj-U4H6lzwzkV90uMFyIXFkGIlqZOTW5LyXXi88IJlz2HjaZt3EtgXmZlol1pEyuFR6PhE1vWtbVcmiopfQT5SiDKBq5yKpnxQ9GchQSp1gSpBkEqHsHedN_lyNZx5x2fSd7T1cS2PRxouzMVBq_itqTV2qLQlRYpT00qa4NI1FS5KbgoI8huaYu66eOOrndWWqWC4ejVjZpH8G46jUOe1nF049plr9AMc_QN-O0jeDEq4fT8GSIRIo2MQK6p59oLrp9p5ucDrTgie2wyffX_x3oNj0jWYxRqBzYW3dK9QVy2MG-HwfcHRmQ5Jw priority: 102 providerName: ProQuest |
| Title | Carrying out streamlined routine data analyses with reports for observational studies: introduction to a series of generic SAS ® macros [version 2; peer review: 2 approved] |
| URI | http://dx.doi.org/10.12688/f1000research.16866.2 https://www.ncbi.nlm.nih.gov/pubmed/31231506 https://www.proquest.com/docview/2249686866 https://www.proquest.com/docview/3182887729 https://pubmed.ncbi.nlm.nih.gov/PMC6567291 https://doaj.org/article/2c8364566a9a4121b17db324b95b6248 |
| Volume | 7 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1baxQxFA61BbEPRetttC5HEHyadSaTuVVE2tJahBaxLiyIhCSTaVfamTq7W-x_En-Ev8xzMrNrV4p98WVZJplkNzk593yHsRdKGYWCR_iGG-0LkUe-RkHtGxspg-LD2JwuOB8cJvsD8X4YD5fYrFxqt4Dja007qic1aE77379dvsUD_8ZhIyRowZXkpO7AcU76YZIlSR_Z8oqLGVE6X6fyf201IuTZdIuao2nohy7Bp_fvoRZkloP2X2WrpSJsjEvqf512-neS5RWptXeXrXXqJmy19HGPLdlqnd0-6ALq62zNVbB8OYYun_A--7GjmobuPkE9nQBdJVFnpIoW0OAD_AKUVArKgZnYMZAjF7rIA6AGDLWeO3px5nE77iaMKCW-aLFqYVKDAiJ-HKAu4Ziwr0cGjraOfv2EM0XLAJ8vWlce8Ndwbm0D7S2bTeDggNAvbPHlARvs7X7a2fe7kg6-EWiE-2FueViUouR5xnOhIsqx5WjTFLHmnAoEBroUIhYGFRmV6iLUsclSroIyTqyw0UO2XNWVfcygTKMsUDYzgUlFiYynDExWFMbwVOdBVnosnm2aNB3eOZXdOJVk99Bmy4XNlm6zJffYq_l75y3ix41vbBNNzHsTYrd7UDfHsmMAkpuMIr5JonIlQh7qMC00arM6j3XCReax6ApFyT9z3DD1xozy5OzsSNTKcmzGDh57Pm9GtkGxIFXZejqWyMo5yhdce489agl1_vsj1GYIeNJj6QIJL_zBxZZqdOKgydE6wCHDJ_9jRZ6yO0QRrb9rgy1Pmql9hhrgRPfYrXSY9tjK9u7hh48950fBz3fDsOcO-287KV4x |
| linkProvider | Scholars Portal |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1bT9RAFD7BJVF5IIq3KuqYaHwqtNPpzYQYQMgiLDECCW_jzHQKm8gWt7sx_AN_jT_BB3-Z53RnC2uMPJF92fQy0_bMnPv5DsBrpYxCwSN8w432hcgjX6Og9o2NlEHxYWxOBc69_aR7JD4ex8dz8GtaC0NplVOe2DDqojLkI19FUZMnGf6S9-fffOoaRdHVaQsN5VorFGsNxJgr7Ni1F9_RhKvXdj4gvd9wvr11uNn1XZcB3wi0C_0wtzwsSlHyPOO5UBGlfXJUs4tYc0496wJdChELg7JVpboIdWyylKugjBMrbITj3oJ5QQ6UDsxvbO1_-tx6eVD_QgmRutJknqC5WZJH3SH5nK6E9EYrfEYqNs0DFmChVIS-cUHX_0v__TuN84pc3L4Hi06hZeuTFXgf5uxgCW73XMh-CRabHplva-YyFh_Aj001HFJ1FavGI0bFKuqMlN2CDfEA_mGUtspUA5dia0auYuZiGwx1bFbp1pWMM9eTcd-xPiXdFxM0XDaqmGK0vXCAqmQnhK7dN-xg_YD9_snOFH2Hh3B0I6R6BJ1BNbBPgJVplAXKZiYwqSiRbZWByYrCGJ7qPMhKD-IpQaRxaOnUtOOrJKuJCClnCCkbQkruwWp73_kEL-TaOzaI3u3VhPfdHKiGJ9KxD8lNRvHiJFG5EiEPdZgWGnVhncc64SLzILqyWuTlHNdMvTxdVdKxrlpebjQPXrWnkelQJEkNbDWuJQoCjtIJv70HjyeLsH3-CHUhgq30IJ1ZnjMvOHtm0D9tgM3RtsAhw6f_f6yXcKd72NuTezv7u8_gLtF94hNbhs5oOLbPUUsc6RduKzL4ctO7_w8Ex3oR |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1bT9RAFJ4gJEQeiOKtijomGp_KttPpzYQYbhsQ2RCRhLdxZjoDm0iL290Y_oG_xh_ho7_Kc9rZwhojT2RfNr3MtD0z5zv3Q8hrKbUE4OG-Zlr5nOeRrwCofW0iqQE-tMkxwflgkOwe8w8n8ckc-T3NhcGwyilPbBh1UWm0kfcAavIkg1_Ssy4s4nC7__7im48dpNDTOm2nIV2bhWK9KTfmkjz2zeV3UOfq9b1toP0bxvo7n7d2fddxwNccdEQ_zA0LC8styzOWcxlhCCgDkbuIFWPYvy5QlvOYa8BZmaoiVLHOUiYDGyeGmwjGvUMWUkB9UAQXNncGh586iw_IYoAWqUtTZgmonhat666qz9laiG-3xmYQsmkksESWrMRKHJd4_b9k4b9DOq9hZP8eWXbCLd1oV-N9MmfKFbJ44Nz3K2S56Zf5tqYuevEB-bElRyPMtKLVZEwxcUWeo-Bb0BEcgD8UQ1ipbEqnmJqi2Zg6PwcFeZtWqjMrw8x1O-47OsQA_KKtjEvHFZUUtxoMUFl6ipW2h5oebRzRXz_pucTv8JAc3wqpHpH5sirNE0JtGmWBNJkOdMotsDAb6KwotGapyoPMeiSeEkRoVzkdG3h8FahBISHFDCFFQ0jBPNLr7rtoa4fceMcm0ru7Gmt_Nweq0alwrEQwnaHvOElkLnnIQhWmhQK5WOWxShjPPBJdWy3iao4bpl6drirh2FgtrjadR151p4EBoVdJlqaa1AJAgQFSwbf3yON2EXbPH4FchCUsPZLOLM-ZF5w9Uw7PmiLnoGfAkOHT_z_WS7IIXEB83BvsPyN3keyteWyVzI9HE_McBMaxeuF2IiVfbnvz_wH_5n5V |
| 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=Carrying+out+streamlined+routine+data+analyses+with+reports+for+observational+studies%3A+introduction+to+a+series+of+generic+SAS%C2%AE+macros+%5Bversion+2%3B+peer+review%3A+2+approved%5D&rft.jtitle=F1000+research&rft.au=Yuan+Liu&rft.au=Dana+C.+Nickleach&rft.au=Chao+Zhang&rft.au=Jeffrey+M.+Switchenko&rft.date=2018&rft.pub=F1000+Research+Ltd&rft.issn=2046-1402&rft.eissn=2046-1402&rft.volume=7&rft_id=info:doi/10.12688%2Ff1000research.16866.2&rft.externalDBID=DOA&rft.externalDocID=oai_doaj_org_article_2c8364566a9a4121b17db324b95b6248 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2046-1402&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2046-1402&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2046-1402&client=summon |