sequential analysis of regression variance
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... Student’s t distribution 80 -- 4.3 X2 distribution 84 to -- VI -- CONTENTS -- Chapter 5 -- 5.1 Regression ... ... lines and equations 89 -- 5.2 Fitting regression lines 95 -- 5.3 Measures of correlation 101 -- 5.4 ... ... Association and dependence 109 -- 5.5 Multiple regression 112 -- 5.6 Rank correlation 116 -- Chapter ... ... sampling 126 -- 6.6 Analysis of variance 131 -- Chapter 7 -- 7.1 Vital statistics 137 -- 7.2 Life tables ... ... and cohort analysis 146 -- 7.3 Computers and medical research 151 -- Index -- 159 ...
First published 162 stran : ilustrace, tabulky ; 23 cm
- MeSH
- statistika jako téma MeSH
- Publikační typ
- monografie MeSH
- Konspekt
- Lékařské vědy. Lékařství
- NLK Obory
- statistika, zdravotnická statistika
... Distributions and Some Standard Notation 2 -- 1.3 Characteristics of a Distribution: Mean, Median and Variance ... ... 119 -- 10 Linear Regression Models for Medical Data 124 -- 10.1 Introduction 124 -- 10.2 A Historical ... ... Note 125 -- 10.3 Multiple Linear Regression 126 -- 10.4 Correlation 131 -- 10.5 The Analysis of Variance ... ... Binary Logistic Regression 141 -- 11.1 Introduction 141 -- 11.2 Logistic Regression 142 -- 11.3 Estimation ... ... in 2X2 Tables 144 -- 11.4 Reanalysis of a Previous Example 149 -- 11.5 The Analysis of Dose-Response ...
2nd ed. 228 s. : il.
- MeSH
- biometrie metody MeSH
- statistika jako téma MeSH
- Publikační typ
- monografie MeSH
- Konspekt
- Demografie. Populace
- NLK Obory
- demografie
- statistika, zdravotnická statistika
QT interval variability, mostly expressed by QT variability index (QTVi), has repeatedly been used in risk diagnostics. Physiologic correlates of QT variability expressions have been little researched especially when measured in short 10-second electrocardiograms (ECGs). This study investigated different QT variability indices, including QTVi and the standard deviation of QT interval durations (SDQT) in 657,287 10-second ECGs recorded in 523 healthy subjects (259 females). The indices were related to the underlying heart rate and to the 10-second standard deviation of RR intervals (SDRR). The analyses showed that both QTVi and SDQT (as well as other QT variability indices) were highly statistically significantly (p < 0.00001) influenced by heart rate and that QTVi showed poor intra-subject reproducibility (coefficient of variance approaching 200%). Furthermore, sequential analysis of regression variance showed that SDQT was more strongly related to the underlying heart rate than to SDRR, and that QTVi was influenced by the underlying heart rate and SDRR more strongly than by SDQT (p < 0.00001 for these comparisons of regression dependency). The study concludes that instead of QTVi, simpler expressions of QT interval variability, such as SDQT, appear preferable for future applications especially if multivariable combination with the underlying heart rate is used.
- Publikační typ
- časopisecké články MeSH
