STRengthening analytical thinking for observational studies: The STRATOS initiative
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STRengthening analytical thinking for observational studies : The STRATOS initiative. / Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G.; le Cessie, Saskia; Carpenter, James; Abrahamowicz, Michal; Andersen, Per Kragh; Altman, Doug; Becher, Heiko; Binder, Harald; Blettner, Maria; Bodicoat, Danielle; Bossuyt, Patrick; Carpenter, James; Carroll, Raymond; Chadha-Boreham, Harbajan; Collins, Gary; De Stavola, Bianca; Duchateau, Luc; Evans, Stephen; Freedman, Laurence; Gail, Mitchell; Goetghebeur, Els; Gustafson, Paul; Harrell, Frank; Huebner, Marianne; Jenkner, Carolin; Kipnis, Victor; Kuechenhoff, Helmut; Cessie, Saskia le; Lee, Kate; Macaskill, Petra; Moodie, Erica; Pearce, Neil; Quantin, Catherine; Rahnenfuehrer, Joerg; Royston, Patrick; Sauerbrei, Willi; Schumacher, Martin; Sekula, Peggy; Stefanski, Len; Steyerberg, Ewout; Therneau, Terry; Tilling, Kate; Vach, Werner; Vickers, Andrew; Wacholder, Sholom; Waernbaum, Ingeborg; White, Ian; Woodward, Mark.
I: Statistics in Medicine, Bind 33, Nr. 30, 30.12.2014, s. 5413-5432.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - STRengthening analytical thinking for observational studies
T2 - The STRATOS initiative
AU - Sauerbrei, Willi
AU - Abrahamowicz, Michal
AU - Altman, Douglas G.
AU - le Cessie, Saskia
AU - Carpenter, James
AU - Abrahamowicz, Michal
AU - Andersen, Per Kragh
AU - Altman, Doug
AU - Becher, Heiko
AU - Binder, Harald
AU - Blettner, Maria
AU - Bodicoat, Danielle
AU - Bossuyt, Patrick
AU - Carpenter, James
AU - Carroll, Raymond
AU - Chadha-Boreham, Harbajan
AU - Collins, Gary
AU - De Stavola, Bianca
AU - Duchateau, Luc
AU - Evans, Stephen
AU - Freedman, Laurence
AU - Gail, Mitchell
AU - Goetghebeur, Els
AU - Gustafson, Paul
AU - Harrell, Frank
AU - Huebner, Marianne
AU - Jenkner, Carolin
AU - Kipnis, Victor
AU - Kuechenhoff, Helmut
AU - Cessie, Saskia le
AU - Lee, Kate
AU - Macaskill, Petra
AU - Moodie, Erica
AU - Pearce, Neil
AU - Quantin, Catherine
AU - Rahnenfuehrer, Joerg
AU - Royston, Patrick
AU - Sauerbrei, Willi
AU - Schumacher, Martin
AU - Sekula, Peggy
AU - Stefanski, Len
AU - Steyerberg, Ewout
AU - Therneau, Terry
AU - Tilling, Kate
AU - Vach, Werner
AU - Vickers, Andrew
AU - Wacholder, Sholom
AU - Waernbaum, Ingeborg
AU - White, Ian
AU - Woodward, Mark
PY - 2014/12/30
Y1 - 2014/12/30
N2 - The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even 'standard' analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests.In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved.
AB - The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even 'standard' analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests.In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved.
KW - Guidance for analysis
KW - Level of statistical knowledge
KW - Observational studies
U2 - 10.1002/sim.6265
DO - 10.1002/sim.6265
M3 - Journal article
C2 - 25074480
AN - SCOPUS:84918821784
VL - 33
SP - 5413
EP - 5432
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 30
ER -
ID: 135449440