LEADER 03527nam 22006255 450 001 9910299968203321 005 20200705023925.0 010 $a3-319-12550-8 024 7 $a10.1007/978-3-319-12550-3 035 $a(CKB)3710000000404007 035 $a(SSID)ssj0001501737 035 $a(PQKBManifestationID)11918721 035 $a(PQKBTitleCode)TC0001501737 035 $a(PQKBWorkID)11447017 035 $a(PQKB)11471344 035 $a(DE-He213)978-3-319-12550-3 035 $a(MiAaPQ)EBC5589111 035 $a(PPN)185484239 035 $a(EXLCZ)993710000000404007 100 $a20150417d2014 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical Literacy for Clinical Practitioners /$fby William H. Holmes, William C. Rinaman 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (XI, 485 p. 340 illus.) 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-319-12549-4 327 $aOverview -- The Evidence Pyramid -- Case Study -- Case-control Study -- Randomized Controlled Trial -- Meta-analysis -- References -- Exercise Questions. 330 $aThis textbook on statistics is written for students in medicine, epidemiology, and public health. It builds on the important role evidence-based medicine now plays in the clinical practice of physicians, physician assistants and allied health practitioners. By bringing research design and statistics to the fore, this book can integrate these skills into the curricula of professional programs. Students, particularly practitioners-in-training, will learn statistical skills that are required of today?s clinicians. Practice problems at the end of each chapter and downloadable data sets provided by the authors ensure readers get practical experience that they can then apply to their own work.  Topics covered include:   Functions of Statistics in Clinical Research Common Study Designs Describing Distributions of Categorical and Quantitative Variables Confidence Intervals and Hypothesis Testing Documenting Relationships in Categorical and Quantitative Data< Assessing Screening and Diagnostic Tests Comparing Means of Independent and Related Samples Linear Regression Binary Logistic Regression Survival Analysis Regression Analysis of Count Data. 606 $aStatistics 606 $aMedicine 606 $aEpidemiology 606 $aStatistics for Life Sciences, Medicine, Health Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17030 606 $aMedicine/Public Health, general$3https://scigraph.springernature.com/ontologies/product-market-codes/H00007 606 $aEpidemiology$3https://scigraph.springernature.com/ontologies/product-market-codes/H63000 615 0$aStatistics. 615 0$aMedicine. 615 0$aEpidemiology. 615 14$aStatistics for Life Sciences, Medicine, Health Sciences. 615 24$aMedicine/Public Health, general. 615 24$aEpidemiology. 676 $a618 700 $aHolmes$b William H$4aut$4http://id.loc.gov/vocabulary/relators/aut$0313007 702 $aRinaman$b William C$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299968203321 996 $aStatistical Literacy for Clinical Practitioners$92495549 997 $aUNINA