William Sribney
Autore di Maximum Likelihood Estimation with Stata, Third Edition
Opere di William Sribney
Etichette
Informazioni generali
- Nome legale
- Sribney, William Michael
- Data di nascita
- 1954
- Sesso
- male
- Nazionalità
- USA
- Luogo di nascita
- USA
- Luogo di residenza
- White Lake, New York, USA
- Istruzione
- University of North Carolina (MS Biostatistics ∙ 1992)
- Attività lavorative
- biostatistician
statistical software developer - Organizzazioni
- Wayne State University
University of Southern California
University California, Los Angeles
Third Way Statistics
Harcourt Brace Jovanovich
North American Vegetarian Society (mostra tutto 8)
Boston Vegetarian Society
Triangle Vegetarian Society, Chapel Hill, North Carolina, USA - Breve biografia
- William Sribney, MS – Author, The role of patient activation on patient–provider communication and quality of care for US- and foreign-born Latino patients
William Sribney is Vice President of Third Way Statistics. He holds an MS in Biostatistics (1992) from the University of North Carolina at Chapel Hill. He is a biostatistician who works with biomedical, epidemiological, and genetics researchers. He is also a professional developer of commercial statistical software. He currently works as a consulting statistician and part‐time as a statistical software developer at Third Way Statistics. He has special expertise in the selection and development of data measures, the analysis of complex survey data, and in the development of software for performing these analyses. For the past five years, Mr. Sribney has worked extensively analyzing results from national health surveys, with special focus on the health of Latinos and other minority populations inthe US, and has co‐authored 14 publications in this area in during this period.
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Statistiche
- Opere
- 1
- Utenti
- 21
- Popolarità
- #570,576
- Voto
- 4.0
- Recensioni
- 1
- ISBN
- 5
New ml commands and their functions:
constraint: fits a model with linear constraints on the coefficient by defining your constraints; accepts a constraint matrix
ml model: picks up survey characteristics; accepts the subpop option for analyzing survey data
optimization algorithms: Berndt-Hall-Hall-Hausman (BHHH), Davidon-Fletcher-Powell (DFP), Broyden-Fletcher-Goldfarb-Shanno (BFGS)
ml: switches between optimization algorithms; computes variance estimates using the outer product of gradients (OPG)… (altro)