Difference between revisions of "Scientific Methods for Health Sciences"

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This section describes the means of traversing, searching, discovering and utilizing the SMHS EBook resources in both formal and informal learning setting.
 
This section describes the means of traversing, searching, discovering and utilizing the SMHS EBook resources in both formal and informal learning setting.
  
===[[EBook_copyright | Copyrights]]===
+
===[[SMHS_copyright | Copyrights]]===
 
The SMHS EBook is a freely and openly accessible electronic book developed by SOCR and the general community.
 
The SMHS EBook is a freely and openly accessible electronic book developed by SOCR and the general community.
  

Revision as of 16:56, 25 June 2014

Contents

SOCR Wiki: Scientific Methods for Health Sciences

Scientific Methods for Health Sciences EBook


Electronic book (EBook) on Scientific Methods for Health Sciences (coming up ...)

Preface

This is an electronic Internet-based Scientific Methods for Health Sciences (SMHS) EBook. The materials, tools and demonstrations presented in this EBook may be helpful to learners, instructors and scientists involved in biomedical, healthcare, Big Data, and informatics studies. The EBook is initially developed by the University of MIchigan Statistics Online Computational Resource (SOCR). However, many students, faculty, educators and member of the community participate, and others are encouraged to take part, in expanding, improving and validating the content of these learning materials.

There are 4 novel features of this specific EBook. It is community-built, completely open-access (in terms of use and contributions), blends information technology, scientific techniques and modern pedagogical concepts, and is multilingual.

Format

Follow the instructions in this page to expand, revise or improve the materials in this EBook.

Learning and Instructional Usage

This section describes the means of traversing, searching, discovering and utilizing the SMHS EBook resources in both formal and informal learning setting.

Copyrights

The SMHS EBook is a freely and openly accessible electronic book developed by SOCR and the general community.

Chapter I: Fundamentals

Exploratory Data Analysis, Plots and Charts

Ubiquitous variation

Parametric inference

Probability Theory

Odds Ratio/Relative Risk

Probability Distributions

Resampling/Simulation

Design of Experiments

Intro to Epidemiology

Experiments vs. Observational studies

Estimation

Hypothesis

Data management

Statistical Power, sample-size, effect-size, sensitivity, specificity

Bias/Precision

Association vs. Causality

Rate-of-change

Clinical vs. Stat significance

Statistical Independence Bayesian Rule

Chapter II: Applied Inference

Epidemiology

Correlation/SLR (ρ and slope inference, 1-2 samples)

ROC Curve

ANOVA

Non-parametric inference

Cronbach's α

Measurement Reliability/Validity

Survival Analysis

Decision theory

CLT/LLNs – limiting results and misconceptions

Association Tests

Bayesian Inference

PCA/ICA/Factor Analysis

Point/Interval Estimation (CI) – MoM, MLE

Instrument performance Evaluation

Study/Research Critiques

Common mistakes and misconceptions in using probability and statistics, identifying potential assumption violations, and avoiding them

Chapter III: Linear Modeling

MLR Regression

GLM

ANOVA

ANCOVA

MANOVA

MANCOVA

Repeated measures ANOVA

(Partial) Correlation

Time series analysis

Fixed, randomized and mixed models

Hierarchical Linear Models

Multi-Model Inference

Mixture modeling

Surveys

Longitudinal data

Generalized Estimating Equations (GEE) models

Model Fitting and Model Quality (KS-test)

Chapter IV: Special Topics

Scientific Visualization

PCOR/CER methods Heterogeneity of Treatment Effects

Big-Data/Big-Science

Missing data

Genotype-Environment-Phenotype associations

Medical imaging

Data Networks

Adaptive Clinical Trials

Databases/registries

Meta-analyses

Causality/Causal Inference, SEM

Classification methods

Time-series analysis

Scientific Validation

Geographic Information Systems (GIS)

Rasch measurement model/analysis

MCMC sampling for Bayesian inference

Network Analysis




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