Statistics for the Health Sciences

Dancey and Reidy are very well known for their Pearson textbook Statistics Without Maths for Psychology and have applied the same principles here to the health sciences market, where they're far more established as researchers.

Klappentext Dancey and Reidy are very well known for their Pearson textbook Statistics Without Maths for Psychology and have applied the same principles here to the health sciences market, where they're far more established as researchers. Zusammenfassung Dancey and Reidy are very well known for their Pearson textbook Statistics Without Maths for Psychology and have applied the same principles here to the health sciences market, where they're far more established as researchers. Inhaltsverzeichnis PART ONE: AN INTRODUCTION TO THE RESEARCH PROCESS Overview The Research Process Concepts and Variables Levels of Measurement Hypothesis Testing Evidence-Based Practice Research Designs Multiple-Choice Questions PART TWO: COMPUTER-ASSISTED ANALYSIS Overview Overview of the Three Statistical Packages Introduction to SPSS Setting out Your Variables for within - and between-Group Designs Introduction to R Introduction to SAS Summary Exercises PART THREE: DESCRIPTIVE STATISTICS Overview Anaylsing Data Descriptive Statistics Numerical Descriptive Statistics Choosing a Measure of Central Tendency Measures of Variation or Dispersion Deviations from the Mean Numerical Descriptives in SPSS Graphical Statistics Bar Charts Line Graphs Incorporating Variability into Graphs Generating Graphs with Standard Deviations in SPSS Graphs Showing Dispersion - Frequency Histogram Box-Plots Summary SPSS Exercise Multiple Choice Questions PART FOUR: THE BASIS OF STATISTICAL TESTING Overview Introduction Samples and Populations Distributions Statistical Significance Criticisms of NHST Generating Confidence Intervals in SPSS Summary SPSS Exercise Multiple Choice Questions PART FIVE: EPIDEMIOLOGY Overview Introduction Estimating the Prevalence of Disease Difficulties in Estimating Prevalence Beyond Prevalence: Identifying Risk Factors for Disease Risk Ratios The Odds-Ratio Establishing Causality Case-Control Studies Cohort Studies Experimental Designs Summary Multiple Choice Questions PART SIX: INTRODUCTION TO DATA SCREENING AND CLEANING Overview Introduction Minimising Problems at the Design Stage Entering Data into Databases/Statistical Packages The Dirty Dataset Accuracy Using Descriptive Statistics to Help Identify Errors Missing Data Spotting Missing Data Normality Screening Groups Separately Reporting Data Screning and Cleaning Procedures Summary Multiple Choice Questions PART SEVEN: DIFFERENCES BETWEEN TWO GROUPS Overview Introduction Conceptual Description of the t-Tests Generalising to the Population Independent Groups t-Test in SPSS Cohen s d Paired t-Test in SPSS Two-Sample z-Test Non-Parametric Tests Mann-Whitney: for Independent Groups Mann-Whitney Test in SPSS Wilcoxon Signed Rank Test: For Repeated Measures Wilcoxon Signed Rank Test in SPSS Adjusting for Multiple Tests Summary Multiple Choice Questions PART EIGHT: DIFFERENCES BETWEEN THREE OR MORE CONDITIONS Overview Introduction Conceptual Description of the (Parametric) ANOVA One-Way ANOVA One-way ANOVA in SPSS ANOVA Models for Repeated-Measures Designs Repeated Measures ANOVA in SPSS Non-parametric Equivalents The Kruskal-Wallis Test Kruskal-Wallis and the Median Test in SPSS The Median Test Friedman s ANOVA for Repeated Measures Friedman s ANOVA in SPSS Summary Multiple Choice Questions PART NINE: TESTING ASSOCIATIONS BETWEEN CATEGORICAL VARIABLES Overview Introduction Rationale of Contingency Table Analysis Running the Analysis in SPSS Measuring Effect Size in Contingency Table Analysis Larger Conting...

Inhalt

PART ONE: AN INTRODUCTION TO THE RESEARCH PROCESS
Overview
The Research Process
Concepts and Variables
Levels of Measurement
Hypothesis Testing
Evidence-Based Practice
Research Designs
Multiple-Choice Questions
PART TWO: COMPUTER-ASSISTED ANALYSIS
Overview
Overview of the Three Statistical Packages
Introduction to SPSS
Setting out Your Variables for within - and between-Group Designs
Introduction to R
Introduction to SAS
Summary
Exercises
PART THREE: DESCRIPTIVE STATISTICS
Overview
Anaylsing Data
Descriptive Statistics
Numerical Descriptive Statistics
Choosing a Measure of Central Tendency
Measures of Variation or Dispersion
Deviations from the Mean
Numerical Descriptives in SPSS
Graphical Statistics
Bar Charts
Line Graphs
Incorporating Variability into Graphs
Generating Graphs with Standard Deviations in SPSS
Graphs Showing Dispersion - Frequency Histogram
Box-Plots
Summary
SPSS Exercise
Multiple Choice Questions
PART FOUR: THE BASIS OF STATISTICAL TESTING
Overview
Introduction
Samples and Populations
Distributions
Statistical Significance
Criticisms of NHST
Generating Confidence Intervals in SPSS
Summary
SPSS Exercise
Multiple Choice Questions
PART FIVE: EPIDEMIOLOGY
Overview
Introduction
Estimating the Prevalence of Disease
Difficulties in Estimating Prevalence
Beyond Prevalence: Identifying Risk Factors for Disease
Risk Ratios
The Odds-Ratio
Establishing Causality
Case-Control Studies
Cohort Studies
Experimental Designs
Summary
Multiple Choice Questions
PART SIX: INTRODUCTION TO DATA SCREENING AND CLEANING
Overview
Introduction
Minimising Problems at the Design Stage
Entering Data into Databases/Statistical Packages
The Dirty Dataset
Accuracy
Using Descriptive Statistics to Help Identify Errors
Missing Data
Spotting Missing Data
Normality
Screening Groups Separately
Reporting Data Screning and Cleaning Procedures
Summary
Multiple Choice Questions
PART SEVEN: DIFFERENCES BETWEEN TWO GROUPS
Overview
Introduction
Conceptual Description of the t-Tests
Generalising to the Population
Independent Groups t-Test in SPSS
Cohen s d
Paired t-Test in SPSS
Two-Sample z-Test
Non-Parametric Tests
Mann-Whitney: for Independent Groups
Mann-Whitney Test in SPSS
Wilcoxon Signed Rank Test: For Repeated Measures
Wilcoxon Signed Rank Test in SPSS
Adjusting for Multiple Tests
Summary
Multiple Choice Questions
PART EIGHT: DIFFERENCES BETWEEN THREE OR MORE CONDITIONS
Overview
Introduction
Conceptual Description of the (Parametric) ANOVA
One-Way ANOVA
One-way ANOVA in SPSS
ANOVA Models for Repeated-Measures Designs
Repeated Measures ANOVA in SPSS
Non-parametric Equivalents
The Kruskal-Wallis Test
Kruskal-Wallis and the Median Test in SPSS
The Median Test
Friedman s ANOVA for Repeated Measures
Friedman s ANOVA in SPSS
Summary
Multiple Choice Questions
PART NINE: TESTING ASSOCIATIONS BETWEEN CATEGORICAL VARIABLES
Overview
Introduction
Rationale of Contingency Table Analysis
Running the Analysis in SPSS
Measuring Effect Size in Contingency Table Analysis
Larger Contingency Tables
Contingency Table Analysis Assumptions
The X2 Goodness of Fit Test
Running the X2 Goodness of Fit Test Using SPSS
Summary
Multiple Choice Questions
PART TEN: MEASURING AGREEMENT: CORRELATIONAL TECHNIQUES
Overview
Introduction
Bivariate Relationships
Perfect Correlations
Calculating the Correlation Pearson s R Using SPSS.
How to obtain Scatterplots
Variance Explanation of R
Obtaining Correlational Analysis in SPSS: Exercise
Partial Correlations
Shared and Unique Variance: Conceptual Understanding Relating to Partial Corrections
Spearman s Rho
Other uses for Correlational Techniques
Reliability of Measures
Internal Consistency
Inter Rater Reliability
Validity
Percentage Agreement
Cohen s Kappa
Summary
Multiple Choice Questions
PART 11: LINEAR REGRESSION
Overview
Introduction
Linear Regression in SPSS
Obtaining teh Scatterplot with Regression Line and Confidence Intervals in SPSS
Assumptions Underlying Line…