Introduction to Statistical Analysis of Laboratory Data (eBook)

Alfred A. Bartolucci is Professor Emeritus in the Department of Biostatistics, School of Public Health, University of Alabama at Birmingham. He has over 300 peer-reviewed publications (manuscripts and book chapters) in the areas of original statistical methodologic research and clinical and laboratory statistical applications. An endowed scholarship in Biostatistics at UAB was established in his honor. Karan P. Singh is currently Professor of Medicine and serves as Director of the Biostatistics and Bioinformatics Shared Facility at the University of Alabama at Birmingham Comprehensive Cancer Center. He has authored or coauthored over 250 peer-reviewed articles, book chapters, and peer-reviewed congress or conference proceedings. He is a Fellow of the American Statistical association. Sejong Bae is Professor of Medicine and serves as Co-Director of the Biostatistics and Bioinformatics Shared Facility; Deputy Director of the Coronary Artery Risk Development in Young Adults Coordination Center; and Director of Data, Information, and Statistics Core in the Division of Preventive Medicine. In 2009, he was elected to International Statistical Institute.

Descriptive Statistics

1.1 Measures of Central Tendency

1.2 Measures of Variation

1.3 Laboratory Example

1.4 Putting it All Together

1.5 Summary

Distributions and Hypothesis Testing in Formal Statistical Laboratory Procedures

2.1 Introduction

2.2 Confidence Intervals

2.3 Inferential Statistics - Hypothesis Testing

Method Validation

3.1 Introduction

3.2 Accuracy

3.4 Sensitivity, Specificity (Selectivity)

3.5 Method Validation and Method Agreement - Bland Altman

Methodologies in Outlier Analysis

4.1 Introduction

4.2 Some Outlier Determination Techniques

4.3. Combined Method Comparison Outlier Analysis

4.4 Some Consequences Of Outlier Removal

4.5 Considering Outlier Variance

Statistical Process Control

5.1 Introduction

5.2 Control Charts

5.3 Capability Analysis

5.4 Capability Analysis - An Alternate Consideration

Limits of Calibration

6.1 Calibration: Limit Strategies for Laboratory Assay Data

6.2 Limit Strategies

6.3 Method Detection Limits (EPA)

6.4 Data Near The Detection Limits

6.5 More on Statistical Management of Non Detects

6.6 The Kaplan-Meier Method (Non-Parametric Approach) for Analysis of Lab Data with Non-Detects

Calibration Bias

7. 1 Error

7.2 Uncertainty

7.3 Sources of Uncertainty

7.4 Estimation Methods of Uncertainty

7.5 Calibration Bias

7.6 Multiple Instruments

7.7 Crude vs. Precise Methodologies

Robustness and Ruggedness

8.1 Introduction

8.2 Robustness

8.3 uggedness

8.4 An Alternative Procedure for Ruggedness Determination

8.5 Ruggedness and System Suitability Tests

"The book presents a detailed discussion of important statistical concepts and methods of data presentation and analysis.
-Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process.
- Introduces terminology used in many applications such as the interpretation of assay design and validation as well as fit for purpose" procedures including real world examples." (Zentralblatt MATH 2016)