Biometry.
Overview
| Works: | 129 works in 61 publications in 61 languages | |
|---|---|---|
Titles
Clinical biostatistics : = an introduction to evidence-based medicine /
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Regression methods in biostatistics : = linear, logistic, survival, and repeated measures models /
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Regression Methods in Biostatistics = Linear, Logistic, Survival, and Repeated Measures Models /
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Biometric systems for data analysis = design, evaluation, and data mining /
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Regression methods in biostatistics = linear, logistic, survival, and repeated measures models /
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(Electronic resources)
Introduction to data analysis and graphical presentation in biostatistics with R = statistics in the large /
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Simultaneous statistical inference = with applications in the life sciences /
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Excel 2016 for biological and life sciences statistics = a guide to solving practical problems /
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Frontiers of biostatistical methods and applications in clinical oncology
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Objective biometric methods for the diagnosis and treatment of nervous system disorders
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Studying a study and testing a test = reading evidence-based health research /
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Phylogenetic trees and molecular evolution = a hands-on introduction with uncertainty quantification corrected /
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Biometry = the principles and practice of statistics in biological research
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Biostatistics : = a foundation for analysis in the health sciences /
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Statistics and experimental design : = an introduction for biologists and biochemists /
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Biometry : = the principles and practice of statistics in biological research /
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Statistical methods for rates and proportions / = Joseph L. Fleiss, Bruce Levin, Myunghee Cho Paik.
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Basic epidemiological methods and biostatistics = a practical guidebook /
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Biostatistics and epidemiology = a primer for health and biomedical professionals /
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Biostatistik : = [eine Einfuhrung fur Biologen und Agrarwissenschaftler] /
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Cause and correlation in biology = a user's guide to path analysis, structural equations, and causal inference /
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Biostatistics for radiologists = planning, performing, and writing a radiologic study /
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The biostatistics cookbook = the most user-friendly guide for the bio/medical scientist /
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Biostatistics with R = an introduction to statistics through biological data /
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Recent advances in biostatistics = false discovery rates, survival analysis, and related topics /
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Cause and Correlation in Biology : = A User's Guide to Path Analysis, Structural Equations and Causal Inference.
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Practical biostatistics = a user-friendly approach for evidence-based medicine /
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Statistical approaches to orofacial pain and temporomandibular disorders research
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Statistical modelling in biostatistics and bioinformatics = selected papers /
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Bayesian phylogenetics : = methods, algorithms, and applications /
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Progress in pattern recognition, image analysis, computer vision, and applications = 20th Iberoamerican Congress, CIARP 2015, Montevideo, Uruguay, November 9-12, 2015 : proceedings /
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Secure IT systems = 20th Nordic Conference, NordSec 2015, Stockholm, Sweden, October 19-21, 2015 : proceedings /
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An introduction to statistics with Python = with applications in the life sciences /
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Modern dose-finding designs for cancer phase I trials = drug combinations and molecularly targeted agents /
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Methods and biostatistics in oncology = understanding clinical research as an applied tool /
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Pattern recognition and machine intelligence = 7th International Conference, PReMI 2017, Kolkata, India, December 5-8, 2017 : proceedings /
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Excel 2019 for biological and life sciences statistics = a guide to solving practical problems /
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(Electronic resources)
Statistical modeling in biomedical research = contemporary topics and voices in the field /
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Biometric identification technologies based on modern data mining methods
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Regression analysis in medical research = for Starters and 2nd Levelers /
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Computational and methodological statistics and biostatistics = contemporary essays in advancement /
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An introduction to statistics with Python = with applications in the life sciences /
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Practical biostatistics = a step-by-step approach for evidence-based medicine /
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Generalized linear mixed models with applications in agriculture and biology
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Advances in clinical immunology, medical microbiology, COVID-19, and Big data
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Introduction to data science in biostatistics = using R, the tidyverse ecosystem, and APIs /
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Statistical causal inferences and their applications in public health research
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Repeated measures design with generalized linear mixed models for randomized controlled trials /
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