September 2000Department of Statistics Kansas State University 1 Statistics and Design of Experiments: Role in Research George A. Milliken, PhD Department.

Slides:



Advertisements
Similar presentations
Educational Research: Causal-Comparative Studies
Advertisements

Chapter 2 The Process of Experimentation
Randomized Complete Block and Repeated Measures (Each Subject Receives Each Treatment) Designs KNNL – Chapters 21,
Statistics : Role in Research. Statistics: A collection of procedures and processes to enable researchers in the unbiased pursuit of Knowledge Statistics.
LSU-HSC School of Public Health Biostatistics 1 Statistical Core Didactic Introduction to Biostatistics Donald E. Mercante, PhD.
Copyright © 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 12 Measures of Association.
1 Dr. Jerrell T. Stracener EMIS 7370 STAT 5340 Probability and Statistics for Scientists and Engineers Department of Engineering Management, Information.
Critiquing Research Articles For important and highly relevant articles: 1. Introduce the study, say how it exemplifies the point you are discussing 2.
Lecture 10 PY 427 Statistics 1 Fall 2006 Kin Ching Kong, Ph.D
Causal Comparative Research: Purpose
Statistics: The Science of Learning from Data Data Collection Data Analysis Interpretation Prediction  Take Action W.E. Deming “The value of statistics.
8. ANALYSIS OF VARIANCE 8.1 Elements of a Designed Experiment
13-1 Designing Engineering Experiments Every experiment involves a sequence of activities: Conjecture – the original hypothesis that motivates the.
L1 Chapter 11 Experimental and Quasi- experimental Designs Dr. Bill Bauer.
Nasih Jaber Ali Scientific and disciplined inquiry is an orderly process, involving: problem Recognition and identification of a topic to.
Go to Table of ContentTable of Content Analysis of Variance: Randomized Blocks Farrokh Alemi Ph.D. Kashif Haqqi M.D.
Introduction to the design (and analysis) of experiments James M. Curran Department of Statistics, University of Auckland
13 Design and Analysis of Single-Factor Experiments:
T WO W AY ANOVA W ITH R EPLICATION  Also called a Factorial Experiment.  Factorial Experiment is used to evaluate 2 or more factors simultaneously. 
T WO WAY ANOVA WITH REPLICATION  Also called a Factorial Experiment.  Replication means an independent repeat of each factor combination.  The purpose.
Fig Theory construction. A good theory will generate a host of testable hypotheses. In a typical study, only one or a few of these hypotheses can.
Choosing Statistical Procedures
I want to test a wound treatment or educational program but I have no funding or resources, How do I do it? Implementing & evaluating wound research conducted.
AP Statistics Section 5.2 A Designing Experiments
Chapter 2: The Research Enterprise in Psychology
Chapter 2: The Research Enterprise in Psychology
Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc Chapter 24 Statistical Inference: Conclusion.
بسم الله الرحمن الرحيم * this presentation about :- “experimental design “ * Induced to :- Dr Aidah Abu Elsoud Alkaissi * Prepared by :- 1)-Hamsa karof.
Research Methodology For IB Psychology Students. Empirical Investigation The collecting of objective information firsthand, by making careful measurements.
Research Design. Research is based on Scientific Method Propose a hypothesis that is testable Objective observations are collected Results are analyzed.
The Research Enterprise in Psychology. The Scientific Method: Terminology Operational definitions are used to clarify precisely what is meant by each.
Evaluating a Research Report
The Scientific Method Formulation of an H ypothesis P lanning an experiment to objectively test the hypothesis Careful observation and collection of D.
The Scientific Method in Psychology.  Descriptive Studies: naturalistic observations; case studies. Individuals observed in their environment.  Correlational.
Identifying the Split-plot and Constructing an Analysis George A. Milliken Department of Statistics Kansas State University
Techniques of research control: -Extraneous variables (confounding) are: The variables which could have an unwanted effect on the dependent variable under.
1 Chapter 3: Experimental Design. 2 Effect of Wine Consumption on Heart Disease Death Rate **Each data point represents a different country.
The Research Enterprise in Psychology
The success or failure of an investigation usually depends on the design of the experiment. Prepared by Odyssa NRM Molo.
1 Chapter 13 Analysis of Variance. 2 Chapter Outline  An introduction to experimental design and analysis of variance  Analysis of Variance and the.
The Research Design. Experimental Design Definition A description of what a researcher would like to find out and how to find it out. Pre-requisites 1.Identification.
Why is Research Important?. Basic Research Pure science or research Research for the sake of finding new information and expanding the knowledge base.
Stefano Vezzoli, CROS NT
Chapter 14 Repeated Measures and Two Factor Analysis of Variance
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 14 Comparing Groups: Analysis of Variance Methods Section 14.1 One-Way ANOVA: Comparing.
Chapter 10: Analysis of Variance: Comparing More Than Two Means.
Chapter Seventeen. Figure 17.1 Relationship of Hypothesis Testing Related to Differences to the Previous Chapter and the Marketing Research Process Focus.
Unit 1 Sections 1-1 & : Introduction What is Statistics?  Statistics – the science of conducting studies to collect, organize, summarize, analyze,
RESEARCH METHODS IN INDUSTRIAL PSYCHOLOGY & ORGANIZATION Pertemuan Matakuliah: D Sosiologi dan Psikologi Industri Tahun: Sep-2009.
What is Science? SECTION 1.1. What Is Science and Is Not  Scientific ideas are open to testing, discussion, and revision  Science is an organize way.
1 Simulation Scenarios. 2 Computer Based Experiments Systematically planning and conducting scientific studies that change experimental variables together.
URBDP 591 A Lecture 16: Research Validity and Replication Objectives Guidelines for Writing Final Paper Statistical Conclusion Validity Montecarlo Simulation/Randomization.
1 Topic 14 – Experimental Design Crossover Nested Factors Repeated Measures.
Research Design Quantitative. Quantitative Research Design Quantitative Research is the cornerstone of evidence-based practice It provides the knowledge.
Chapter 2: The Research Enterprise in Psychology.
Uses of Diagnostic Tests Screen (mammography for breast cancer) Diagnose (electrocardiogram for acute myocardial infarction) Grade (stage of cancer) Monitor.
WELCOME TO BIOSTATISTICS! WELCOME TO BIOSTATISTICS! Course content.
STA248 week 121 Bootstrap Test for Pairs of Means of a Non-Normal Population – small samples Suppose X 1, …, X n are iid from some distribution independent.
Factorial Experiments
Statistical Core Didactic
MODULE 2 Myers’ Exploring Psychology 5th Ed.
Observational Study vs. Experimental Design
CHAPTER 2 Research Methods in Industrial/Organizational Psychology
Chapter 10: Analysis of Variance: Comparing More Than Two Means
Statistics for Business and Economics (13e)
The Nature of Probability and Statistics
Philip G. Zimbardo Robert L. Johnson Ann L. Weber
Research Design Quantitative.
DESIGN OF EXPERIMENTS by R. C. Baker
Chapter 10 – Part II Analysis of Variance
Presentation transcript:

September 2000Department of Statistics Kansas State University 1 Statistics and Design of Experiments: Role in Research George A. Milliken, PhD Department of Statistics Kansas State University Manhattan, Kansas

September 2000Department of Statistics Kansas State University 2 Statistics: A collection of procedures and processes to enable researchers in the unbiased pursuit of Knowledge Statistics is an important part of the Scientific Method State a Hypothesis Analyze the Data Design a Study and Collect Data Interpret the Results—Draw Conclusions

September 2000Department of Statistics Kansas State University 3 State a Hypothesis: The OBJECTIVE or OBJECTIVES of the Study A HYPOTHESIS OR SET OF HYPOTHESES should state exactly what you want to DO or LEARN or STUDY SHOULD ANSWER What are the factors to be studied and what relationships are to be investigated? What is the experimental material? Etc.?

September 2000Department of Statistics Kansas State University 4 The area of STATISTICS would not be needed if each time you measured an experimental unit you would obtain the same response or value BUT, THE RESPONSES ARE NOT THE SAME SINCE THERE IS VARIABILITY or NOISE IN THE SYSTEM STATISTICAL METHODS EXTRACT THE SIGNAL FROM THE NOISE TO PROVIDE INFORMATION One of the Statistician’s JOBS is to make sense from DATA in the presence of VARIABILITY or noise by using DATA ANALYSIS TOOLS

September 2000Department of Statistics Kansas State University 5 DESIGN VS. ANALYSIS The PURPOSE OF DATA COLLECTION is to GAIN INFORMATION OR KNOWLEDGE!! Collecting Data does not guarantee that information is obtained. INFORMATION ≠ DATA At best: INFORMATION=DATA+ANALYSIS

September 2000Department of Statistics Kansas State University 6 If data are collected such that they contain NO information in the first place, then the analysis phase cannot find it!!! The best way to insure that appropriate information is contained in the collected data is to DESIGN (plan) and Carefully Control the DATA COLLECTION PROCESS The measured variables must relate to the stated OBJECTIVES of the study

September 2000Department of Statistics Kansas State University 7 If you have a good design and process for data collection, it is quite often straight forward to construct an analysis that extracts all of the available information from the data The ROLE of a STATISTICIAN is to work with the REAEARCH TEAM (or researcher) from the START of the study

September 2000Department of Statistics Kansas State University 8 A STATISTICIAN CAN HELP OBTAIN THE MAXIMUM AMOUNT INFORMATON FROM AVAILABLE RESOURCES The MOST IMPORTANT TIME for the statistician to become involved with a research study is in the very BEGINNING

September 2000Department of Statistics Kansas State University 9 HOW??? HELP WITH THE DESIGN OF THE EXPERIMENT DETERMINE SAMPLE SIZE NEEDED DEVELOP PROCESS OF COLLECTING DATA DISCUSS VARIABLES TO BE MEASURED AND HOW THEY RELATE TO THE OBJECTIVES OF THE STUDY PROVIDE METHODS OF ANALYZING THE DATA HELP TRANSLATE STATISTICAL CONCLUSIONS INTO SUBJECT MATTER CONCLUSIONS

September 2000Department of Statistics Kansas State University 10 THE CORE HELP FROM THE STATISTICIAN IS IN THE DESIGN OF THE EXPERIMENT Help with selecting conditions that relate to the objectives of the study Selecting the Experimental Units Deciding when REPLICATIONS exist Determining the ORDER in which the experiment is to be carried out THE DESIGN OF THE EXPERIMENT IS CRITICAL

September 2000Department of Statistics Kansas State University 11 COMPONENTS OF DESIGNED EXPERIMENTS TREATMENT STRUCTURE: Factors or Populations or Treatments related to the objectives of the experiment: Brands of Product, Types of Uses of Product DESIGN STRUCTURE OR EXPERIMENTAL UNITS: Factors used in blocking the experimental units as well as characteristics of exp. Units Washing Machine, Person Using Machine, Products evaluated in Session by Taste Panelist

September 2000Department of Statistics Kansas State University 12 Complete Designed Experiment Treatment Structure Design Structure RANDOMIZE – randomization plan to assign Treatment of TS to Experimental Units in DS

September 2000Department of Statistics Kansas State University 13 RANDOMIZATION IS THE INSURANCE POLICY AGAINST INTRODUCING BIAS INTO THE STUDY Selecting an appropriate Treatment Structure, necessary Design Structure, and required Randomization Process provides the Statistician the information needed to construct an appropriate model APPROPRIATE MODEL = BEST ANALYSIS

September 2000Department of Statistics Kansas State University 14 Key to the Design of the Experiment is the Concept of REPLICATION REPLICATON: The independent observation of a treatment An Experimental Unit Provides a Replication of the level of a Factor if the level is randomly assigned the the Experimental Unit and observed independently of the other Experimental Units Must make sure that Sub-samples are not considered to be Replications

September 2000Department of Statistics Kansas State University 15 The Variability among Experimental Units treated independently alike provides the estimate of the variance (or Standard Error) to be used as the measuring stick for comparing the levels of treatments randomly assigned to those Experimental Units Between Sub-sample variance is generally much less than between Replication variance It is critical that the Replications are appropriately Identified Treatment Structure, Design Structure (with experimental units and replication) and Randomization describe the total Design

September 2000Department of Statistics Kansas State University 16 ANALYZE THE DATA: Use the COMPLETED DESIGNED EXPERIMENT and the data type to construct an appropriate analysis Use Statistical Software – SAS, RS/1, JMP A software package you know will provide valid results

September 2000Department of Statistics Kansas State University 17 The Statistician will provide the STATISTICAL interpretation of the results from the analyses – STATISTICAL ANALYSES CONCLUSIONS The Statistician will help the Researcher TRANSLATE the statistical analyses conclusions into subject matter conclusions Discuss how the statistical analyses provide results that relate to the STATED OBJECTIVES of the study. The expected results should be written along with the objectives. Results that are not expected should be looked at carefully

September 2000Department of Statistics Kansas State University 18 Washing Machine Example: 4 brands or models -- one machine each 3 types of laundry – Whites, Wash/wear, Denim 3 persons to operate the Machines For each person: Randomly assign the order of Brands For each Brand, randomly assign the order of Types

September 2000Department of Statistics Kansas State University 19 Brand DBrand BBrand ABrand C Random Order of Brands for Person 1 White W/W Denim Machine Random Order of Types within each Machine Re-Randomize for each Person

September 2000Department of Statistics Kansas State University 20 Machines are Experimental Unit for Brands and Variance is computed by Person*Brand Persons are Blocks of Machines Compare BRANDS by using the variability among Machines Treated Alike

September 2000Department of Statistics Kansas State University 21 The Machines within a Person are Blocks for Types – Three Loads per Machine The Loads within a machine are the Experimental Units for Type and Brand*Type Variability among Loads treated alike provides the measuring stick for comparing the levels of Type and Brand*Type This Design Involves Persons as Blocks and Two Sizes of Experimental Unit Machine and Load

September 2000Department of Statistics Kansas State University 22 If you ignore that this design involves TWO sizes of Experimental Units and there are Two Error Terms, the resulting error term is a combination of these two error terms The combined error term is Too Large for making comparisons involving Type and Brand*Type – won’t find things that are there The Combined error term is Too Small for Making comparisons involving Brand – will declare things to be different when they are not Statistical Conclusions can be very misleading

September 2000Department of Statistics Kansas State University 23 STATISTICIAN’S JOB – to figure out how the study is being ran and help identify the type of design that is being used which includes determining if more than one size of experimental unit is involved This is accomplished BEST when the Statistician is involved at the Beginning of the Study

September 2000Department of Statistics Kansas State University 24 SALSA TASTING EXPERIMENT NINE TYPES OR BRANDS OF SALSA A PERSON CAN TASTE ONLY THREE SALSAS DURING THE SESSION TWELVE PERSONS WILL BE USED IN THE STUDY

September 2000Department of Statistics Kansas State University 25 ASSIGNMENT OF PRODUCTS TO PERSONS – with orderPerson Order CAB 7FDE 2HIG 8AGD 3EBH9CIF 4GBF10DHC 5IEA11FAH 6CGE12BDI

September 2000Department of Statistics Kansas State University 26 Each Product is Tasted 4 times – there are Four Replications of each product Since each person tastes only Three of the products, how do we compare the products? The Analysis obtains predicted values for each Product for each Person Want to compare the Products as if each Person had tasted all of the Products

September 2000Department of Statistics Kansas State University 27 The Product Means of these Predicted Values are the “ADJUSTED MEANS” for each Product Called LEAST SQUARES MEANS by SAS ® The LSMEANS are the Predicted Means as if Each of the Persons has Tasted and evaluated all of the products

September 2000Department of Statistics Kansas State University 28 Some times characteristics of experimental units are measured – to be used as possible covariates Study the effect of three types of Drugs on a persons heart rate Randomly Assign 12 persons to each of the Drugs -- person is experimental unit Dose the person with the assigned drug and measure the heart rate after 15 minutes

September 2000Department of Statistics Kansas State University 29 Persons do not have identical heart rates before being given the respective drug Measure the initial heart rate – heart rate before giving the drug We want to compare the Drugs as if all experimental units (persons) had the same initial heart rate

September 2000Department of Statistics Kansas State University 30 Analysis of Covariance uses a regression model to obtain predicted after drug heart rate values as if all persons had initial heart rates of, say, 74 beats per minute The Drug Means of these predicted heart rates are used to compare the Drugs – These means of Predicted Values are called LSMEANS

September 2000Department of Statistics Kansas State University 31 LSMEANS are adjusted means and occur in several venues 1.Obtain treatments’ means when not all treatments are observed the same number of times by each person 2.Obtain treatments’ means when the experimental units do not have identical values of the covariates

September 2000Department of Statistics Kansas State University 32 Another Role of the Statistician is to provide appropriate models for the analysis of the data from a given study in order to take into account the Design Structure and covariates to provide estimates of the treatment effects as if all experimental units had observed all treatments or all experimental units had the same value of the covariate -- provide appropriate LSMEANS

September 2000Department of Statistics Kansas State University 33 Involving the Statistician in the Beginning of the Study will 1.improve the chance of conducting a successful experiment 2.Speed up the turn around of the analyses since was involved with the design 3.Reduce the costs associated with the experiment -- making sure the sample size is adequate to provide the needed detectable differences

September 2000Department of Statistics Kansas State University 34 THE END THANK YOU FOR LISTENING