LEADER 00717nam0-22002651i-450- 001 990005759860403321 005 19990530 035 $a000575986 035 $aFED01000575986 035 $a(Aleph)000575986FED01 035 $a000575986 100 $a19990530d1903----km-y0itay50------ba 101 0 $aita 105 $ay-------001yy 200 1 $aApofonia consonantica$fAttilio Levi 210 $aTorino$cCarlo Clausen$d1903 215 $a102 p.$d24 cm 700 1$aLevi,$bAttilio$f<1863->$0191957 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990005759860403321 952 $aGLOTT. B V e 17$bIST.GLOTT. S.I.$fFLFBC 959 $aFLFBC 996 $aApofonia consonantica$9570389 997 $aUNINA LEADER 03112nam 22004935 450 001 9910254486303321 005 20200630162638.0 010 $a3-319-39586-6 024 7 $a10.1007/978-3-319-39586-9 035 $a(CKB)3710000000837847 035 $a(DE-He213)978-3-319-39586-9 035 $a(MiAaPQ)EBC6315168 035 $a(MiAaPQ)EBC5578830 035 $a(Au-PeEL)EBL5578830 035 $a(OCoLC)958069401 035 $a(PPN)194806685 035 $a(EXLCZ)993710000000837847 100 $a20160823d2017 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aUnderstanding Clinical Data Analysis $eLearning Statistical Principles from Published Clinical Research /$fby Ton J. Cleophas, Aeilko H. Zwinderman 205 $a1st ed. 2017. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (X, 234 p. 211 illus., 92 illus. in color.) 311 $a3-319-39585-8 327 $aPreface -- Randomness -- Randomized and Observational Research -- Randomized Clinical Trials, Designs -- Randomized Clinical Trials, Analysis Sets, Statistical Analysis, Reporting Issues -- Discrete Data Analysis, Failure Time Data Analysis -- Quantitative Data Analysis -- Subgroup Analysis -- Interim Analysis -- Multiplicity Analysis -- Medical Statistics, a Discipline at the Interface of Biology and Mathematics.-Index. 330 $aThis textbook consists of ten chapters, and is a must-read to all medical and health professionals, who already have basic knowledge of how to analyze their clinical data, but still, wonder, after having done so, why procedures were performed the way they were. The book is also a must-read to those who tend to submerge in the flood of novel statistical methodologies, as communicated in current clinical reports, and scientific meetings. In the past few years, the HOW-SO of current statistical tests has been made much more simple than it was in the past, thanks to the abundance of statistical software programs of an excellent quality. However, the WHY-SO may have been somewhat under-emphasized. For example, why do statistical tests constantly use unfamiliar terms, like probability distributions, hypothesis testing, randomness, normality, scientific rigor, and why are Gaussian curves so hard, and do they make non-mathematicians getting lost all the time? The book will cover the WHY-SOs. 606 $aMedicine 606 $aMedicine/Public Health, general$3https://scigraph.springernature.com/ontologies/product-market-codes/H00007 615 0$aMedicine. 615 14$aMedicine/Public Health, general. 676 $a610 700 $aCleophas$b Ton J$4aut$4http://id.loc.gov/vocabulary/relators/aut$0472359 702 $aZwinderman$b Aeilko H$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254486303321 996 $aUnderstanding Clinical Data Analysis$92534542 997 $aUNINA