Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Regression methods for medical research / / Bee Choo Tai, David Machin
| Regression methods for medical research / / Bee Choo Tai, David Machin |
| Autore | Tai Bee-Choo |
| Pubbl/distr/stampa | Chichester, West Sussex, UK : , : John Wiley and Sons, , 2014 |
| Descrizione fisica | 1 online resource (313 p.) |
| Disciplina | 610.72/4 |
| Altri autori (Persone) | MachinDavid <1939-> |
| Soggetto topico |
Regression analysis
Medicine - Research |
| ISBN |
1-118-72198-5
1-118-72195-0 1-118-72196-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Regression Methods for Medical Research; Copyright; Contents; Preface; 1 Introduction; Introduction; Statistical models; Comparing two means; Linear regression; Types of dependent variables (y-variables); Some completed studies; Further reading; Technical details; Student's t-test; Linear regression; Predicting a mean value of y for a particular x; Predicting an individual's value of y for a particular x; Analysis of Variance (ANOVA); Coefficient of determination; Extending the simple linear model; Correlation; Logarithms and the exponential constant, e
2 Linear Regression: Practical IssuesTypes of covariates (independent variables); Ordered categorical covariates; Numerically discrete covariates; Unordered categorical covariates; Verifying the assumptions; Ordered categorical covariate; Continuous covariate; Do the assumptions matter?; Precautions; Computation; Simple models; Study design; Clinical and statistical significance; Reporting; Technical details; Global tests; Ordered Normal scores; 3 Multiple Linear Regression; Linear regression: two covariates; How good is the fitted model?; Quadratic models; Multiple linear regression Extending the 2-covariate modelNotation; Interactions; Non-nested models; Precautions; Nested models; Collinearity; Parsimonious models; Verifying assumptions; Technical details; Nested models; Akaike's criterion; 4 Logistic Regression; The logit transformation; Odds ratio; The logit transformation; Logistic regression; Categorical and continuous covariates; Unordered categorical covariate; Ordered categorical covariate; Continuous covariate; Multiple logistic regression; Interactions; Model checking; Tabulations; Lack of an important covariate; Outlying or influential observations Goodness-of-fitConditional logistic regression; Ordered logistic regression; Technical details; Odds ratio (OR) and relative risk (RR); Binomial distribution; Maximum likelihood estimation (MLE); Likelihood ratio (LR) test; The empirical logit transformation; 5 Poisson Regression; Introduction; Poisson or Binomial models; Unknown population size at risk; Over-dispersion and robust estimates; Over-dispersion; Robust procedures; Known population size at risk; Known cumulative exposure; Zero-inflated models; Residuals; Technical details; Poisson distribution; Maximum Likelihood Estimation (MLE) Relationship between Poisson and logit models6 Time-to-Event Regression; Time-to-event data; Kaplan-Meier survival curve; The hazard rate and hazard ratio; Hazard ratio; The Cox regression model; Single covariate; Two covariates; More than two covariates; Verifying proportional hazards; Complementary log-log plot; Observed and predicted K-M plots; Schoenfeld residuals; What if the proportional hazards assumption is wrong?; Stratified Cox; Technical details; Calculating a Kaplan-Meier survival curve; The hazard function; The complementary log-log transformation; Residuals; 7 Model Building Introduction |
| Record Nr. | UNINA-9910138997503321 |
Tai Bee-Choo
|
||
| Chichester, West Sussex, UK : , : John Wiley and Sons, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Regression methods for medical research / / Bee Choo Tai, David Machin
| Regression methods for medical research / / Bee Choo Tai, David Machin |
| Autore | Tai Bee-Choo |
| Pubbl/distr/stampa | Chichester, West Sussex, UK : , : John Wiley and Sons, , 2014 |
| Descrizione fisica | 1 online resource (313 p.) |
| Disciplina | 610.72/4 |
| Altri autori (Persone) | MachinDavid <1939-> |
| Soggetto topico |
Regression analysis
Medicine - Research |
| ISBN |
1-118-72198-5
1-118-72195-0 1-118-72196-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Regression Methods for Medical Research; Copyright; Contents; Preface; 1 Introduction; Introduction; Statistical models; Comparing two means; Linear regression; Types of dependent variables (y-variables); Some completed studies; Further reading; Technical details; Student's t-test; Linear regression; Predicting a mean value of y for a particular x; Predicting an individual's value of y for a particular x; Analysis of Variance (ANOVA); Coefficient of determination; Extending the simple linear model; Correlation; Logarithms and the exponential constant, e
2 Linear Regression: Practical IssuesTypes of covariates (independent variables); Ordered categorical covariates; Numerically discrete covariates; Unordered categorical covariates; Verifying the assumptions; Ordered categorical covariate; Continuous covariate; Do the assumptions matter?; Precautions; Computation; Simple models; Study design; Clinical and statistical significance; Reporting; Technical details; Global tests; Ordered Normal scores; 3 Multiple Linear Regression; Linear regression: two covariates; How good is the fitted model?; Quadratic models; Multiple linear regression Extending the 2-covariate modelNotation; Interactions; Non-nested models; Precautions; Nested models; Collinearity; Parsimonious models; Verifying assumptions; Technical details; Nested models; Akaike's criterion; 4 Logistic Regression; The logit transformation; Odds ratio; The logit transformation; Logistic regression; Categorical and continuous covariates; Unordered categorical covariate; Ordered categorical covariate; Continuous covariate; Multiple logistic regression; Interactions; Model checking; Tabulations; Lack of an important covariate; Outlying or influential observations Goodness-of-fitConditional logistic regression; Ordered logistic regression; Technical details; Odds ratio (OR) and relative risk (RR); Binomial distribution; Maximum likelihood estimation (MLE); Likelihood ratio (LR) test; The empirical logit transformation; 5 Poisson Regression; Introduction; Poisson or Binomial models; Unknown population size at risk; Over-dispersion and robust estimates; Over-dispersion; Robust procedures; Known population size at risk; Known cumulative exposure; Zero-inflated models; Residuals; Technical details; Poisson distribution; Maximum Likelihood Estimation (MLE) Relationship between Poisson and logit models6 Time-to-Event Regression; Time-to-event data; Kaplan-Meier survival curve; The hazard rate and hazard ratio; Hazard ratio; The Cox regression model; Single covariate; Two covariates; More than two covariates; Verifying proportional hazards; Complementary log-log plot; Observed and predicted K-M plots; Schoenfeld residuals; What if the proportional hazards assumption is wrong?; Stratified Cox; Technical details; Calculating a Kaplan-Meier survival curve; The hazard function; The complementary log-log transformation; Residuals; 7 Model Building Introduction |
| Record Nr. | UNINA-9910811547103321 |
|
Tai Bee-Choo
|
||
| Chichester, West Sussex, UK : , : John Wiley and Sons, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||