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Statistics for the Health Sciences: A Non-Mathematical Introduction

Statistics for the Health Sciences: A Non-Mathematical Introduction

Autorzy
Wydawnictwo SAGE Publications Ltd
Data wydania 19/03/2012
Liczba stron 584
Forma publikacji książka w miękkiej oprawie
Poziom zaawansowania Dla szkół wyższych i kształcenia podyplomowego
Język angielski
ISBN 9781849203364
Kategorie Sprzęt medyczny i techniki
367.50 PLN (z VAT)
$82.67 / €78.79 / £68.40 /
Produkt na zamówienie
Dostawa 3-4 tygodnie
Ilość
Do schowka

Opis książki

Statistics for the Health Sciences is a highly readable and accessible textbook on understanding statistics for the health sciences, both conceptually and via the SPSS programme. The authors give clear explanations of the concepts underlying statistical analyses and descriptions of how these analyses are applied in health science research without complex maths formulae.





The textbook takes students from the basics of research design, hypothesis testing and descriptive statistical techniques through to more advanced inferential statistical tests that health science students are likely to encounter. The strengths and weaknesses of different techniques are critically appraised throughout, and the authors emphasise how they may be used both in research and to inform best practice care in health settings.





Exercises and tips throughout the book allow students to practice using SPSS. The companion website provides further practical experience of conducting statistical analyses. Features include:





* multiple choice questions for both student and lecturer use


* full Powerpoint slides for lecturers


* practical exercises using SPSS


* additional practical exercises using SAS and R





This is an essential textbook for students studying beginner and intermediate level statistics across the health sciences. 'Statistics for the Health Sciences engagingly presents the key analytic issues that students and professionals need to understand in the most accessible and vivid way possible. Full of real examples and practical exercises, the book successfully avoids getting bogged down with complex maths and formulae' -
Dennis Howitt at Loughborough University



The chapter overviews, absence of statistical formulae and use of appropriate examples and student exercises make this a very 'hands on' and practical text' -



Merryl E Harvey, Birmingham City University

Statistics for the Health Sciences: A Non-Mathematical Introduction

Spis treści

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 Linear Regression

Dealing with Outliers

What happens if the Correlation Between X and Y is Near Zero?

Using Regression to Predict Missing Data in SPSS

Prediction of Missing Scores on Cognitive Failures in SPSS

Summary

Multiple-Choice Questions

PART TWELVE: STANDARD MULTIPLE REGRESSION

Overview

Introduction

Multiple Regression in SPSS

Variables in the Equation

The Regression Equation

Predicting an Individual's Score

Hypothesis Testing

Other Types of Multiple Regression

Hierarchical Multiple Regression

Summary

Multiple Choice Questions

PART THIRTEEN: LOGISTIC REGRESSION

Overview

Introduction

The Conceptual Basis of Logistic Regression

Writing up the Result

Logistic Regression with Multiple Predictor Variables

Logistic Regression with Categorical Predictors

Categorical Predictors with Three or More Levels

Summary

Multiple Choice Questions

Interventions and Analysis of Change

Overview

Interventions

How do we Know Whether Interventions are Effective?

Randomised Control Trials (RCTs)

Designing an RCT: CONSORT

The CONSORT Flow Chart

Important Features of an RCT

Blinding

Analysis of RCTs

Running an ANCOVA in SPSS

McNemar's Test of Change

Running McNemar's Test in SPSS

The Sign Test

Running the Sign Test using SPSS

Intention to Treat Analysis

Crossover Designs

Single Case Designs (N= 1)

Generating Single Case Design Graphs Using SPSS

Summary

SPSS Exercise

Multiple Choice Questions

PART FIFTEEN: SURVIVAL ANALYSIS: AN INTRODUCTION

Overview

Introduction

Survival Curves

The Kaplan-Meier Survival Function

Kaplan-Meier Survival Analyses in SPSS

Comparing Two Survival Curves - the Mantel-Cox test

Mantel-Cox using SPSS

Hazard

Hazard Curves

Hazard Functions in SPSS

Writing up a Survival Analysis

Summary

SPSS Exercise

Multiple Choice Questions

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