• Zamawiaj do paczkomatu
  • Płać wygodnie
  • Obniżka
Applied Longitudinal Data Analysis for Medical Science: A Practical Guide

Applied Longitudinal Data Analysis for Medical Science: A Practical Guide

9781009288033
314,94 zł
283,44 zł Zniżka 31,50 zł Brutto
Najniższa cena w okresie 30 dni przed promocją: 283,44 zł
Ilość
Od 4 do 6 tygodni

  Dostawa

Wybierz Paczkomat Inpost, Orlen Paczkę, DPD, Pocztę, email (dla ebooków). Kliknij po więcej

  Płatność

Zapłać szybkim przelewem, kartą płatniczą lub za pobraniem. Kliknij po więcej szczegółów

  Zwroty

Jeżeli jesteś konsumentem możesz zwrócić towar w ciągu 14 dni*. Kliknij po więcej szczegółów

Opis
Essential for non-statisticians and researchers working with longitudinal data from medical studies, this updated new edition discusses the most important techniques available for analysing data of this type. Using non-technical language, the book explores simple methods such as the paired t-test and summary statistics as well as more sophisticated regression-based methods, including mixed model analysis. The emphasis of the discussion lies in the interpretation of the results of these different methods, covering data analysis with continuous, dichotomous, categorical and other outcome variables. Datasets used throughout the book are provided, enabling readers to re-analyse the examples as they make their way through chapters and improve their understanding of the material. Finally, an extensive and practical overview of, and comparison between, different software packages is provided. Readers will be able to use this book as a practical manual in their everyday work without needing a strong background in statistics.
Szczegóły produktu
98060
9781009288033
9781009288033

Opis

Rok wydania
2023
Numer wydania
3
Oprawa
miękka foliowana
Liczba stron
300
Wymiary (mm)
175.00 x 252.00
Waga (g)
500
  • 1. Introduction; 2. Continuous outcome variables; 3. Continuous outcome variables - regression based methods; 4. The modelling of time; 5. Models to disentangle the between- and within-subjects relationship; 6. Causality in observational longitudinal studies; 7. Dichotomous outcome variables; 8. Categorical and count outcome variables; 9. Outcome variables with floor or ceiling effects; 10. Analysis of longitudinal intervention studies; 11. Missing data in longitudinal studies; 12. Sample size calculations; 13. Software for longitudinal data analysis.
Komentarze (0)