Statistical Methods in Laboratory Medicine
Free Global Shipping
No minimum orderDescription
Statistical Methods in Laboratory Medicine focuses on the application of statistics in laboratory medicine. The book first ponders on quantitative and random variables, exploratory data analysis (EDA), probability, and probability distributions. Discussions focus on negative binomial distribution, non-random distributions, binomial distribution, fitting the binomial model to sample data, conditional probability and statistical independence, rules of probability, and Bayes' theorem. The text then examines inference, regression, and measurement and control. Topics cover analytical goals for assay precision, estimating the error variance components, indirect structural assays, functional assays, bivariate regression model, and least-squares estimates of the functional relation parameters. The manuscript takes a look at assay method comparison studies, multivariate analysis, forecasting and control, and test interpretation. Concerns include time series structure and terminology, polynomial regression, assessing the performance of the classification rule, quantitative screening tests, sample correlation coefficient, and computer assisted diagnosis. The book is a dependable reference for medical experts and statisticians interested in the employment of statistics in laboratory medicine.
Table of Contents
Preface
1 Introduction
2 Getting the Picture
2.1 Quantitative Variables
2.3 Random Variables
2.4 Measures
2.5 Collecting the Right Data
2.6 Looking at Sample Data
2.7 The Histogram
2.8 Central Tendency
2.9 Scatter
2.10 Exploratory Data Analysis (EDA)
References
Software
3 Probability
3.1 Introduction
3.2 A State of Nature
3.3 A State of Mind
3.4 Axioms of Probability: Terminology
3.5 Axioms of Probability
3.6 Conditional Probability and Statistical Independence
3.7 Rules of Probability
3.8 Bayes’ Theorem
3.9 Odds and Ends
References
4 Probability Distributions I: Discrete Variables
4.1 Getting the Picture
4.2 The Binomial Distribution
4.3 Fitting the Binomial Model to Sample Data
4.4 The Poisson Distribution
4.5 Non-Random Distributions
4.6 The Negative Binomial Distribution
4.7 Final Thoughts
References
5 Probability Distributions II: Continuous Variables
5.1 The Normal Distribution
5.2 Probability Density
5.3 Fitting the Normal Distribution Function
5.4 Testing the Normal Model Assumption
5.5 Transformations of Non-Normal Data
5.6 Other Distributions
References
6 Inference I
6.1 Populations and Samples
6.2 Survey and Experiment
6.3 Sample Selection: Surveys
6.4 Sampling for Experiment
6.5 From Numbers to Knowledge
6.6 Hypothesis Testing
6.7 Sample Size: Inference on a Single Population Mean
6.8 Comparing Two Independent Samples
6.9 Paired Comparisons
6.10 Non-Parametric Tests
6.11 More than Two Samples
References
7 Regression I: Straight-Line Relationships
7.1 Introduction
7.2 The Nature of Relationships
7.3 Functional Relationships
7.4 Least-Squares Estimates Of The Functional Relation Parameters
7.5 From Arithmetic to Inference
7.6 Inference on the Linear Regression Model
7.7 The Calibration Problem
7.8 Weighted Regression
7.9 The Bivariate Regression Model
7.10 Through the Looking Glass
7.11 Rank Correlation
7.12 Looking Ahead
References
8 Measurement and Control
8.1 Introduction
8.2 Accuracy
8.3 Functional Assays
8.4 Structural Assays
8.5 Indirect Structural Assays
8.6 The Origins of Inaccuracy
8.7 Analytical Goals for Assay Accuracy
8.8 Precision
8.9 Estimating the Error Variance Components
8.10 Analytical Goals for Assay Precision
8.11 Control
8.12 Cumulative Sum Charts (CUSUMS)
8.13 Patient-Based Imprecision Studies
8.14 Patients' Daily Means
8.15 Qualitative Test Control
8.16 A Parting Thought
References
9 Assay Method Comparison Studies
9.1 Introduction
9.2 The Statistical Problem
9.3 A Little History
9.4 Calculations
9.5 Cautions
9.6 The Sample Correlation Coefficient
9.7 Final Thoughts
References
10 Test Interpretation
10.1 Introduction
10.2 A Quest for the Fabulous Norm
10.3 The 95% Reference Paradox
10.4 Multi Variate Reference Ranges
10.5 Screening
10.6 Qualitative Screening Tests
10.7 Quantitative Screening Tests
10.8 Assessing the Individual Patient
10.9 Kernel Density Estimation
10.10 Computer Assisted Diagnosis
References
11 Multivariate Analysis
11.1 Introduction
11.2 Linear Discriminant Function
11.3 Multivariate Normal Discrimination
11.4 Assessing the Performance of the Classification Rule
11.5 Assessing the Individual Patient
11.6 Quadratic Discrimination and Beyond
11.7 Variable Selection
11.8 Regression Revisited
11.9 Polynomial Regression
11.10 Is there a Pattern?
References
12 Forecasting And Control
12.1 Introduction
12.2 Time Series Structure and Terminology
12.3 Recursive Estimation
12.4 The Ewma Discount Coefficient W
12.5 Monitoring a Forecasting System
12.6 Following a Trend
12.7 Holt's Local Linear Trend Model
12.8 The Kaiman Filter
12.9 Following a Trend
Appendix 12.A GW-BASIC Program-Tracker
References
13 Inference II: Analysis of 2X2 Tables
13.1 Sampling Models for 2X2 Tables
13.2 The 2X2 Chi-Square Test
13.3 Fisher's Exact Probability Test
13.4 Estimation I: Comparing Proportions
13.5 Estimation I: The Odds-Ratio
13.6 Paired Comparisons
13.7 Combining 2X2 Tables
13.8 Multidimensional Problems
13.9 Regression with Counted Proportions
Note 13.A Derivation of a 2X2 X2 Statistic
A Note on Notation
References
Appendix A Statistical Tables A.1 to A.8
Table A.1 2000 Random Digits
Table A.2 Areas Under the Standard Normal Curve
Table A.3 Coefficients and Critical Values: Shapiro-Wilk Test
Table A.4 Percentiles of the t Distribution (Two-Sided)
Table A.5 Upper 100α Percentile Points of the Χ2 Distribution
Table A.6 Percentile Points of the F-Distribution (5%)
Table A.7 Critical Values of the Linear Correlation Coefficient
Table A.8 Random Numbers from a Specified Normal Distribution
Index
Product details
- No. of pages: 552
- Language: English
- Copyright: © Butterworth-Heinemann 1991
- Published: September 16, 1991
- Imprint: Butterworth-Heinemann
- eBook ISBN: 9781483161921
About the Author
P. W. Strike
Ratings and Reviews
There are currently no reviews for "Statistical Methods in Laboratory Medicine"