Statistics Applied to Clinical TrialsSpringer Science & Business Media, 2002 - Broj stranica: 210 This book not only explains classical statistical analyses of clinical trials, but addresses relatively novel issues, including equivalence testing, interim analyses, sequential analyses, and meta-analyses, and provides a framework of the best statistical methods currently available for such purposes. The book is not only useful for investigators involved in the field of clinical trials, but also for all physicians who wish to better understand the data of trials. |
Što ljudi govore - Napišite recenziju
Na uobičajenim mjestima nismo pronašli nikakve recenzije.
Sadržaj
III | 1 |
IV | 17 |
V | 39 |
VI | 45 |
VIII | 51 |
IX | 63 |
XI | 71 |
XII | 81 |
XV | 117 |
XVI | 131 |
XVIII | 141 |
XX | 155 |
XXIII | 164 |
XXIV | 165 |
XXV | 175 |
XXVII | 189 |
Ostala izdanja - Prikaži sve
Statistics Applied to Clinical Trials Ton J. M. Cleophas,Aeilko H. Zwinderman,Toine F. Cleophas Pregled nije dostupan - 2002 |
Statistics Applied to Clinical Trials Ton J. M. Cleophas,Aeilko H. Zwinderman,Toine F. Cleophas Pregled nije dostupan - 2002 |
Uobičajeni izrazi i fraze
according actual addition adjustment analysis angina ANOVA approach approximately assessed better blood pressure calculated called carryover effect chance chapter chi-square clinical trials coefficient compared comparisons conclusions considered continuous correlation covariates crossover curve defined demonstrated dependent determinants difference distant drug efficacy equivalence error estimate example expressed factors Figure genes given gives graph groups important increased independent individual interim intervals larger less linear regression lower mean measurements method multiple negative normal distribution null hypothesis observations odds ratio outcome p-value paired particular patients pectoris performed period placebo population positive possible probability problem procedure proportions provides randomized regression reject response risk sample scores SEMs sensitivity shows significant similar square standard statistical subjects Table treatment effect usually validity values variables variance variation zero