2-Group Multivariate Research & Analyses
|
|
- Egbert Hampton
- 5 years ago
- Views:
Transcription
1 2-Group Multivariate Research & Analyses Research Designs Research hypotheses Outcome & Research Hypotheses Outcomes & Truth Significance Tests & Effect Sizes Multivariate designs Increased effects Increased specificity Considering confounds Research Designs True Experiments If well-done, can be used to test causal RH: -- alternative hyp. are ruled out because there are no confounds!!! Non-Experiments No version can be used to test causal RH: -- can t rule out alternative hyp. Because there are confounds!! What designs go with what types of RH:???? True Experiment random assignment of individual participants by researcher before IV manip (helps eliminate confounds) treatment/manipulation performed by researcher (helps eliminate confounds) good control of procedural variables during task completion & DV measurement (helps eliminate confounds) Quasi-Experiment no random assignment of individuals (no confound control) treatment/manipulation performed by researcher poor or no control of procedural variables during task, etc. (no confound control) Natural Groups Design also called Concomitant Measures or Correlational Design no random assignment of ind. (no confound control) no treatment manipulation performed by researcher (all variables are measured) -- a comparison among participants already in groups (no confound control) no control of procedural variables during task, etc. (no confound control) Basic Statistical Designs - BG vs. WG Between Subjects (Between Groups) each subject completes 1 of the IV conditions different groups each complete 1 of the IV conditions Within-subjects (Within-groups, Repeated Measures) each subject completes all of the IV conditions one group of subjects completes all of the IV conditions Design Language For both Between & Within designs, we refer to the IV and the DV Typically the IV ( causal variable ) is qualitative Typically the DV ( effect variable ) is quantitative SPSS Language Between Groups Designs the IV is the grouping variable -- which IV condition each subject was in the DV is the response variable and tells each participant s score on the DV Within-groups Designs there is no IV -- each variable is referred to as a DV there is one DV score for each IV condition each DV score tells the participant s score in that IV condition
2 ANOVA Between Groups (Independent Samples, etc.) H0: Populations represented by the IV conditions have the same mean DV. degrees of freedom (df) numerator = 1, denominator = N - 2 Range of values 0 to Reject Ho: If F obtained > F critical or If p <.05 Within-groups (Dependent Samples, etc.) H0: Populations represented by the IV conditions have the same mean DV. degrees of freedom (df) numerator = 1, denominator = N - 1 Range of values 0 to Reject Ho: If F obtained > F critical or If p <.05 Types of Research Hypotheses Attributive Hypothesis -- a construct (phenomena, behavior, etc.) exists an operational definition of the construct a system to measure the construct demonstration that the construct can be differentiated from other (related) constructs Associative Hypothesis -- two constructs are related (i.e., knowing the value of one provides information about the value of the other) demonstration of a statistical relationship between the variables used to measure the constructs specific statistical analysis is not important, as long as it is appropriate to the data and the expression of the research hypothesis Causal Hypothesis -- the value of one construct influences (causes, produces, etc.) the value of the other construct temporal precedence -- operation of IV comes before measurement of DV no alternative hypotheses (no design flaws, confounds, alternative explanations of the results, etc.) statistical relationship between IV and DV The types of RH: are hierarchically arranged!! Posing a causal hypothesis assumes the associative hypothesis that the IV and DV are related -- if two things aren t related then one can cause the other Posing an associative hypothesis assumes support for the attributive hypothesis of each construct/variable-- unmeasureable things can t be statistically analyzed
3 2-group RH: and outcomes BG & WG... There are only three possible Research Hypotheses Outcomes G1 < G2 G1 = G2 and three possible statistical outcomes Research Hypotheses G1 < G2 G1 = G2 G1 > G2 Keep in mind that rejecting H0: does not guarantee support for the research hypothesis? Why not??? The direction of the mean difference might be opposite that of the RH: G1 > G2 The RH: might be that s there s no difference (RH: = H0:) So, there are only 9 possible combinations of RH: & Outcomes of 3 types effect as expected unexpected null/effect backward effect Also replication of findings is important, even when you get what you expect!! 2-group outcomes & truth... In the population there are only three possibilities... and three possible statistical decisions Decisions G1 < G2 G1 = G2 G1 > G2 In the Population G1 < G2 G1 = G2 G1 > G2 Correctly rejected H0: Type II Type III Type I Correctly retained H0: Type I Type III Type II Correctly rejected H0: Please note that this is a different question than whether the results match the RH: This is about whether the results from the sample are correct whether the results are right. This is about statistical conclusion validity
4 The 9 outcomes come in 5 types Type I -- false alarm - finding a significant mean difference between the conditions in the study when there really isn t a difference between the populations Type II -- miss - finding no difference between the conditions of the study when there really is a difference between the populations Type III -- misspecification - finding a difference between the conditions of the study that is different from the the difference between the populations Correctly retained H0: -- finding no difference between the conditions of the study when there really is no difference between the populations Correctly rejected H0: -- finding a difference between the conditions of the study that is the same as the the difference between the populations Practice with statistical decision s evaluated by comparing our finding with other research the same as those in the Control group. However, the other 10 studies in the field found the Treatment group performed better, better than those in the Control group. This is the same thing the other 10 studies in the field have found. poorer than those in the Control group. But all of the other 10 studies in the field found the opposite effect. better than those in the Control group. But none of the other 10 studies in the field found any difference. the same as those in the Control group. This is the same thing the other 10 studies in the field have found. Type II Correct Reject Type III Type I Correct retain Information from p-values vs. Effect Sizes The p-value (value range 1.0 0) tells the probability of making a Type I if you reject the H0: based on the data from this sample e.g., p =.10 means if we reject H0: based on these data there is a 10% chance that there really is no relationship between the variables in the population represented by the sample The usual acceptable risk is less than 5% or p <.05 Effect size estimates (value range 0 1.0) tell how much of the variability in the DV is accounted for ( predicted from or caused by ) the IV e.g., r =.30 means we estimate that.30 2 or 9% of the variability in the DV is accounted for by the IV large enough to be interesting effect sizes vary with research topics and design types, but a common guideline is.1 = small,.3 = medium and.5 = large
5 Calculating & Using Effect Sizes For 2-group ANOVA (BG or WG) r = F / (F + df ) Where we go from here... 2-group designs with a single DV Significance Test p <.05 p >.05 Effect Size large enough too small to be interesting to be interesting Best case big enough & probably really there Which to believe? Rem - w/ small N comes lowered confidence in the replicability of r Easier to believe r if it replicates earlier research then the large p-value is probably small N Be careful about dismissing these many small effects have turned out to be important Best case too small to care about & probably not really there 2-group designs with a multiple DVs Factorial designs (2+ IVs) single DV multiple DVs multiple-group designs single DV multiple DVs Knowing the design & statistical analyses to directly test any research hypothesis involving treatment mean comparisons!!! Multivariate Research -- when there are multiple DVs Advantages of Multivariate Research Increasing the Number of Effects in theresearch by including measures of multiple possible effects, we have a greater chance of finding an effect -- something that is influenced by or related to the IV e.g., If the IV were some sort of clinical treatment, using the Beck Depression Inventory & State Anxiety Measure & Somatic Complaint Scale gives us a better chance of detecting some type of improvement than would using just one of these research is costly (time & $) -- multiple measures typically add little to the cost but increase the chances of finding something
6 Advantages of Multivariate Research, cont. Increasing the specificity of the effects we find there is no one measure that is the perfect representation of the effect we are studying -- different measures of the same thing often are only moderately correlated (r =.3-.5) using multiple related DVs allows us to more precisely define what is the effect e.g., If the construct DV under study were anxiety, we might want to have measures of anxiety physiological measures, self-report measures, observational measures that we we can better specify what we mean when we say the treatment decreases anxiety because we can say what types of anxiety showed the effect and which didn t Advantages of Multivariate Research, cont. Combining the Two Approaches in a Single Study multiple indices of multiple constructs - give the most precise and dependable results - greater chance of finding something influenced by IV - greater specificity about what is (& isn t) influenced by IV - replication is still important by using Beck Depression Inventory, MMPI Depression Scale, MCMI Depression Scale, State Anxiety Measure, Trait Anxiety Measure, Somatic Complaint Scale, MMPI Hypochondriasis Scale would allow us to determine if the treatment is specific to depression (& what kind ), or includes anxiety and/or somatic complaints (& what kinds ) Using Multiple DVs in Quasi-Experimental and Natural Groups Designs Remember that confounds come in two kinds subject variable confounds IV groups start with different means, on something like age, education, personality attributes or motivation procedural variable confounds during IV manipulation or DV measurement, something besides the IV is done differently between the IV conditions, like instructions, amount of stimulus exposure or practice The presence of either type of confound interferes with the causal interpretation that mean differences on the DV indicate an effect of the IV confounds provide an alternative hypothesis about what caused the DV differences for the IV conditions
7 Using Multiple DVs in Quasi-Experimental and Natural Groups Designs, cont. Measuring subject variables that you fear may be subject variable confounds can help any subject variable that does have a mean difference between IV conditions is a subject variable confound -- can t causally interpret the results of the study!!! that subject variable is an alternative hypothesis any subject variable that does not have a mean difference between the IV conditions can t possibly be a confounding subject variable remember that a subject variable working against the IV is a confound (technically), but does not refute that the IV may be causing the effect! you can t give a causal interpretation to the study, but you can establish whether or not a particular subject variable is a likely alternative hypothesis Multivariate approach to confound evaluation Design is a quasi-experiment w/o random assignment of participants 2 different kinds of exam prep Intended DV % correct on the exam % grade on last exam GPA prior to this class Exam prep time (hrs) Credit card interest rate -- looks pretty good! -- effect in same direction a likely confound -- no effect can t be confound of the IV-DV relationship -- a confound (even though not inflating the IV/DV relationship) a statistical confound relationship to DV is either complicated or spurious Tx control p r 89% 78% % 77%
Research Designs. Internal Validity
Reviewing a few things Research Designs Review of a few things Demonstrations vs. Comparisons Experimental & Non-Experimental Designs IVs and DVs Between Group vs. Within-Group Designs Kinds of bivariate
More informationIntroduction to Path Analysis
Introduction to Path Analysis Review of Multivariate research & an Additional model Structure of Regression Models & Path Models Direct & Indirect effects Mediation analyses When & some words of caution
More informationChapter 11 Nonexperimental Quantitative Research Steps in Nonexperimental Research
Chapter 11 Nonexperimental Quantitative Research (Reminder: Don t forget to utilize the concept maps and study questions as you study this and the other chapters.) Nonexperimental research is needed because
More informationLimitations of 2-cond Designs
Design Conditions & Variables Limitations of 2-group designs Kinds of Treatment & Control conditions Kinds of Causal Hypotheses Explicating Design Variables Kinds of IVs Identifying potential confounds
More informationExperimental Research in HCI. Alma Leora Culén University of Oslo, Department of Informatics, Design
Experimental Research in HCI Alma Leora Culén University of Oslo, Department of Informatics, Design almira@ifi.uio.no INF2260/4060 1 Oslo, 15/09/16 Review Method Methodology Research methods are simply
More information9 research designs likely for PSYC 2100
9 research designs likely for PSYC 2100 1) 1 factor, 2 levels, 1 group (one group gets both treatment levels) related samples t-test (compare means of 2 levels only) 2) 1 factor, 2 levels, 2 groups (one
More informationMultiple Regression Models
Multiple Regression Models Advantages of multiple regression Parts of a multiple regression model & interpretation Raw score vs. Standardized models Differences between r, b biv, b mult & β mult Steps
More informationOne-Way ANOVAs t-test two statistically significant Type I error alpha null hypothesis dependant variable Independent variable three levels;
1 One-Way ANOVAs We have already discussed the t-test. The t-test is used for comparing the means of two groups to determine if there is a statistically significant difference between them. The t-test
More informationPsychology Research Process
Psychology Research Process Logical Processes Induction Observation/Association/Using Correlation Trying to assess, through observation of a large group/sample, what is associated with what? Examples:
More informationExperimental Research. Types of Group Comparison Research. Types of Group Comparison Research. Stephen E. Brock, Ph.D.
Experimental Research Stephen E. Brock, Ph.D., NCSP California State University, Sacramento 1 Types of Group Comparison Research Review Causal-comparative AKA Ex Post Facto (Latin for after the fact).
More informationANCOVA with Regression Homogeneity
ANCOVA with Regression Homogeneity The purpose of the study was to compare the effectiveness of two different treatments in two populations. Both treatments have been repeatedly shown to work better than
More informationChapter 2 Multiple Choice Questions (The answers are provided after the last question.) 1. Which research paradigm is based on the pragmatic view of reality? a. quantitative research b. qualitative research
More informationCHAPTER NINE DATA ANALYSIS / EVALUATING QUALITY (VALIDITY) OF BETWEEN GROUP EXPERIMENTS
CHAPTER NINE DATA ANALYSIS / EVALUATING QUALITY (VALIDITY) OF BETWEEN GROUP EXPERIMENTS Chapter Objectives: Understand Null Hypothesis Significance Testing (NHST) Understand statistical significance and
More informationPsychology Research Process
Psychology Research Process Logical Processes Induction Observation/Association/Using Correlation Trying to assess, through observation of a large group/sample, what is associated with what? Examples:
More informationThe Role and Importance of Research
The Role and Importance of Research What Research Is and Isn t A Model of Scientific Inquiry Different Types of Research Experimental Research What Method to Use When Applied and Basic Research Increasing
More informationInferential Statistics
Inferential Statistics and t - tests ScWk 242 Session 9 Slides Inferential Statistics Ø Inferential statistics are used to test hypotheses about the relationship between the independent and the dependent
More informationConducting a Good Experiment I: Variables and Control
CHAPTER SIX Conducting a Good Experiment I: Variables and Control 1 The Nature of Variables! Variable! A variable is an event or behavior that can assume at least two values.! Bridgman (1927) suggested
More informationResearch Questions, Variables, and Hypotheses: Part 2. Review. Hypotheses RCS /7/04. What are research questions? What are variables?
Research Questions, Variables, and Hypotheses: Part 2 RCS 6740 6/7/04 1 Review What are research questions? What are variables? Definition Function Measurement Scale 2 Hypotheses OK, now that we know how
More informationResearch Process. the Research Loop. Now might be a good time to review the decisions made when conducting any research project.
Research Process Choices & Combinations of research attributes Research Loop and its Applications Research Process and what portions of the process give us what aspects of validity Data Integrity Experimenter
More informationCHAPTER ONE CORRELATION
CHAPTER ONE CORRELATION 1.0 Introduction The first chapter focuses on the nature of statistical data of correlation. The aim of the series of exercises is to ensure the students are able to use SPSS to
More informationLecture 4: Research Approaches
Lecture 4: Research Approaches Lecture Objectives Theories in research Research design approaches ú Experimental vs. non-experimental ú Cross-sectional and longitudinal ú Descriptive approaches How to
More informationSheila Barron Statistics Outreach Center 2/8/2011
Sheila Barron Statistics Outreach Center 2/8/2011 What is Power? When conducting a research study using a statistical hypothesis test, power is the probability of getting statistical significance when
More informationChapter 5: Research Language. Published Examples of Research Concepts
Chapter 5: Research Language Published Examples of Research Concepts Contents Constructs, Types of Variables, Types of Hypotheses Note Taking and Learning References Constructs, Types of Variables, Types
More information9/24/2014 UNIT 2: RESEARCH METHODS AND STATISTICS RESEARCH METHODS RESEARCH METHODS RESEARCH METHODS
RESEARCH METHODS UNIT 2: RESEARCH METHODS AND STATISTICS 8-10% of AP Exam Case Studies A case study is an in-depth study of one person. In a case study, nearly every aspect of the subject's life and history
More informationPolitical Science 15, Winter 2014 Final Review
Political Science 15, Winter 2014 Final Review The major topics covered in class are listed below. You should also take a look at the readings listed on the class website. Studying Politics Scientifically
More informationANTH 260 Introduction to Physical Anthropology LAB
ANTH 260 Introduction to Physical Anthropology LAB Week 2 Lab Instructor/TA: Zach Garfield Washington State University Vancouver Spring 2015 A closer look at variables What s a variable? Qualitative (Discrete/Categorical)
More informationEXPERIMENTAL RESEARCH DESIGNS
ARTHUR PSYC 204 (EXPERIMENTAL PSYCHOLOGY) 14A LECTURE NOTES [02/28/14] EXPERIMENTAL RESEARCH DESIGNS PAGE 1 Topic #5 EXPERIMENTAL RESEARCH DESIGNS As a strict technical definition, an experiment is a study
More informationAnalysis of Variance (ANOVA)
Research Methods and Ethics in Psychology Week 4 Analysis of Variance (ANOVA) One Way Independent Groups ANOVA Brief revision of some important concepts To introduce the concept of familywise error rate.
More informationPrevious Example. New. Tradition
Experimental Design Previous Example New Tradition Goal? New Tradition =? Challenges Internal validity How to guarantee what you have observed is true? External validity How to guarantee what you have
More informationBivariate &/vs. Multivariate
Bivariate &/vs. Multivariate Differences between correlations, simple regression weights & multivariate regression weights Patterns of bivariate & multivariate effects Prox variables Multiple regression
More informationPatrick Breheny. January 28
Confidence intervals Patrick Breheny January 28 Patrick Breheny Introduction to Biostatistics (171:161) 1/19 Recap Introduction In our last lecture, we discussed at some length the Public Health Service
More informationThe t-test: Answers the question: is the difference between the two conditions in my experiment "real" or due to chance?
The t-test: Answers the question: is the difference between the two conditions in my experiment "real" or due to chance? Two versions: (a) Dependent-means t-test: ( Matched-pairs" or "one-sample" t-test).
More informationIndependent Variables Variables (factors) that are manipulated to measure their effect Typically select specific levels of each variable to test
Controlled Experiments experimental investigation of a testable hypothesis, in which conditions are set up to isolate the variables of interest ("independent variables") and test how they affect certain
More informationHypothesis Testing. Richard S. Balkin, Ph.D., LPC-S, NCC
Hypothesis Testing Richard S. Balkin, Ph.D., LPC-S, NCC Overview When we have questions about the effect of a treatment or intervention or wish to compare groups, we use hypothesis testing Parametric statistics
More informationStat 13, Intro. to Statistical Methods for the Life and Health Sciences.
Stat 13, Intro. to Statistical Methods for the Life and Health Sciences. 0. SEs for percentages when testing and for CIs. 1. More about SEs and confidence intervals. 2. Clinton versus Obama and the Bradley
More informationCHAPTER OBJECTIVES - STUDENTS SHOULD BE ABLE TO:
3 Chapter 8 Introducing Inferential Statistics CHAPTER OBJECTIVES - STUDENTS SHOULD BE ABLE TO: Explain the difference between descriptive and inferential statistics. Define the central limit theorem and
More informationTwo-Way Independent ANOVA
Two-Way Independent ANOVA Analysis of Variance (ANOVA) a common and robust statistical test that you can use to compare the mean scores collected from different conditions or groups in an experiment. There
More informationBusiness Statistics Probability
Business Statistics The following was provided by Dr. Suzanne Delaney, and is a comprehensive review of Business Statistics. The workshop instructor will provide relevant examples during the Skills Assessment
More informationPLS 506 Mark T. Imperial, Ph.D. Lecture Notes: Reliability & Validity
PLS 506 Mark T. Imperial, Ph.D. Lecture Notes: Reliability & Validity Measurement & Variables - Initial step is to conceptualize and clarify the concepts embedded in a hypothesis or research question with
More informationRegression Including the Interaction Between Quantitative Variables
Regression Including the Interaction Between Quantitative Variables The purpose of the study was to examine the inter-relationships among social skills, the complexity of the social situation, and performance
More informationRival Plausible Explanations
Ci Criminology i 860 Quasi-Experimentation and Evaluation Research Remember John Stuart Mill s 3 Criteria for inferring the existence of a causal relation: 1. Temporal precedence 2. Existence of a relationship
More informationUnderstanding Statistics for Research Staff!
Statistics for Dummies? Understanding Statistics for Research Staff! Those of us who DO the research, but not the statistics. Rachel Enriquez, RN PhD Epidemiologist Why do we do Clinical Research? Epidemiology
More informationPSYC1024 Clinical Perspectives on Anxiety, Mood and Stress
PSYC1024 Clinical Perspectives on Anxiety, Mood and Stress LECTURE 1 WHAT IS SCIENCE? SCIENCE is a standardised approach of collecting and gathering information and answering simple and complex questions
More informationResearch Methods & Design Outline. Types of research design How to choose a research design Issues in research design
Research Methods & Design Outline Types of research design How to choose a research design Issues in research design Types of Research Design Correlational Field (survey) Experimental Qualitative Meta-analysis
More informationLecture II: Difference in Difference. Causality is difficult to Show from cross
Review Lecture II: Regression Discontinuity and Difference in Difference From Lecture I Causality is difficult to Show from cross sectional observational studies What caused what? X caused Y, Y caused
More informationClever Hans the horse could do simple math and spell out the answers to simple questions. He wasn t always correct, but he was most of the time.
Clever Hans the horse could do simple math and spell out the answers to simple questions. He wasn t always correct, but he was most of the time. While a team of scientists, veterinarians, zoologists and
More informationChapter 8 Experimental Design
Chapter 8 Experimental Design Causality Review Remember from Chapter 4 that in order to make a causal inference, you need to satisfy three requirements: 1. Covariation 2. Temporal order 3. Eliminate alternative
More informationSubstantive Significance of Multivariate Regression Coefficients
Substantive Significance of Multivariate Regression Coefficients Jane E. Miller Institute for Health, Health Care Policy and Aging Research Rutgers University Aims of this talk Provide concrete approaches
More information15.301/310, Managerial Psychology Prof. Dan Ariely Recitation 8: T test and ANOVA
15.301/310, Managerial Psychology Prof. Dan Ariely Recitation 8: T test and ANOVA Statistics does all kinds of stuff to describe data Talk about baseball, other useful stuff We can calculate the probability.
More informationIn this chapter we discuss validity issues for quantitative research and for qualitative research.
Chapter 8 Validity of Research Results (Reminder: Don t forget to utilize the concept maps and study questions as you study this and the other chapters.) In this chapter we discuss validity issues for
More informationDesigning Experiments... Or how many times and ways can I screw that up?!?
www.geo.uzh.ch/microsite/icacogvis/ Designing Experiments... Or how many times and ways can I screw that up?!? Amy L. Griffin AutoCarto 2012, Columbus, OH Outline When do I need to run an experiment and
More informationKepler tried to record the paths of planets in the sky, Harvey to measure the flow of blood in the circulatory system, and chemists tried to produce
Stats 95 Kepler tried to record the paths of planets in the sky, Harvey to measure the flow of blood in the circulatory system, and chemists tried to produce pure gold knowing it was an element, though
More informationResearch Methods in Social Psychology. Lecture Notes By Halford H. Fairchild Pitzer College September 4, 2013
Research Methods in Social Psychology Lecture Notes By Halford H. Fairchild Pitzer College September 4, 2013 Quiz Review A review of our quiz enables a review of research methods in social psychology.
More informationLab 2: The Scientific Method. Summary
Lab 2: The Scientific Method Summary Today we will venture outside to the University pond to develop your ability to apply the scientific method to the study of animal behavior. It s not the African savannah,
More informationHigher Psychology RESEARCH REVISION
Higher Psychology RESEARCH REVISION 1 The biggest change from the old Higher course (up to 2014) is the possibility of an analysis and evaluation question (8-10) marks asking you to comment on aspects
More informationYour goal in studying for the GED science test is scientific
Science Smart 449 Important Science Concepts Your goal in studying for the GED science test is scientific literacy. That is, you should be familiar with broad science concepts and how science works. You
More informationEliminative materialism
Michael Lacewing Eliminative materialism Eliminative materialism (also known as eliminativism) argues that future scientific developments will show that the way we think and talk about the mind is fundamentally
More informationPLANNING THE RESEARCH PROJECT
Van Der Velde / Guide to Business Research Methods First Proof 6.11.2003 4:53pm page 1 Part I PLANNING THE RESEARCH PROJECT Van Der Velde / Guide to Business Research Methods First Proof 6.11.2003 4:53pm
More informationCSC2130: Empirical Research Methods for Software Engineering
CSC2130: Empirical Research Methods for Software Engineering Steve Easterbrook sme@cs.toronto.edu www.cs.toronto.edu/~sme/csc2130/ 2004-5 Steve Easterbrook. This presentation is available free for non-commercial
More informationPSY 216: Elementary Statistics Exam 4
Name: PSY 16: Elementary Statistics Exam 4 This exam consists of multiple-choice questions and essay / problem questions. For each multiple-choice question, circle the one letter that corresponds to the
More informationEmpirical Knowledge: based on observations. Answer questions why, whom, how, and when.
INTRO TO RESEARCH METHODS: Empirical Knowledge: based on observations. Answer questions why, whom, how, and when. Experimental research: treatments are given for the purpose of research. Experimental group
More informationAudio: In this lecture we are going to address psychology as a science. Slide #2
Psychology 312: Lecture 2 Psychology as a Science Slide #1 Psychology As A Science In this lecture we are going to address psychology as a science. Slide #2 Outline Psychology is an empirical science.
More informationDesigning Psychology Experiments: Data Analysis and Presentation
Data Analysis and Presentation Review of Chapter 4: Designing Experiments Develop Hypothesis (or Hypotheses) from Theory Independent Variable(s) and Dependent Variable(s) Operational Definitions of each
More informationComplex Regression Models with Coded, Centered & Quadratic Terms
Complex Regression Models with Coded, Centered & Quadratic Terms We decided to continue our study of the relationships among amount and difficulty of exam practice with exam performance in the first graduate
More informationStill important ideas
Readings: OpenStax - Chapters 1 11 + 13 & Appendix D & E (online) Plous - Chapters 2, 3, and 4 Chapter 2: Cognitive Dissonance, Chapter 3: Memory and Hindsight Bias, Chapter 4: Context Dependence Still
More informationOne slide on research question Literature review: structured; holes you will fill in Your research design
Topics Ahead Week 10-11: Experimental design; Running experiment Week 12: Survey Design; ANOVA Week 13: Correlation and Regression; Non Parametric Statistics Week 14: Computational Methods; Simulation;
More informationConducting Research in the Social Sciences. Rick Balkin, Ph.D., LPC-S, NCC
Conducting Research in the Social Sciences Rick Balkin, Ph.D., LPC-S, NCC 1 Why we do research Improvement Description Explanation Prediction R. S. Balkin, 2008 2 Theory Explanation of an observed phenomena
More informationSources of Variance & ANOVA
ANOVA ANalysis Of VAriance Sources of Variance & ANOVA BG ANOVA Partitioning Variation making F making effect sizes Things that influence F Confounding Inflated within-condition variability Integrating
More information04/12/2014. Research Methods in Psychology. Chapter 6: Independent Groups Designs. What is your ideas? Testing
Research Methods in Psychology Chapter 6: Independent Groups Designs 1 Why Psychologists Conduct Experiments? What is your ideas? 2 Why Psychologists Conduct Experiments? Testing Hypotheses derived from
More informationValidity and Quantitative Research. What is Validity? What is Validity Cont. RCS /16/04
Validity and Quantitative Research RCS 6740 6/16/04 What is Validity? Valid Definition (Dictionary.com): Well grounded; just: a valid objection. Producing the desired results; efficacious: valid methods.
More informationCausal Research Design- Experimentation
In a social science (such as marketing) it is very important to understand that effects (e.g., consumers responding favorably to a new buzz marketing campaign) are caused by multiple variables. The relationships
More informationDescribe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo
Business Statistics The following was provided by Dr. Suzanne Delaney, and is a comprehensive review of Business Statistics. The workshop instructor will provide relevant examples during the Skills Assessment
More informationSelecting Research Participants. Conducting Experiments, Survey Construction and Data Collection. Practical Considerations of Research
Conducting Experiments, Survey Construction and Data Collection RCS 6740 6/28/04 Practical Considerations of Research This lecture will focus on some of the practical aspects of conducting research studies
More information8/28/2017. If the experiment is successful, then the model will explain more variance than it can t SS M will be greater than SS R
PSY 5101: Advanced Statistics for Psychological and Behavioral Research 1 If the ANOVA is significant, then it means that there is some difference, somewhere but it does not tell you which means are different
More informationChapter 11. Experimental Design: One-Way Independent Samples Design
11-1 Chapter 11. Experimental Design: One-Way Independent Samples Design Advantages and Limitations Comparing Two Groups Comparing t Test to ANOVA Independent Samples t Test Independent Samples ANOVA Comparing
More informationAssignment 2: Sampling & Data Analysis COMBINED (Group or Individual Assignment Your Choice)
Assignment 2: Sampling & Data Analysis COMBINED (Group or Individual Assignment Your Choice) Objectives: After completing this assignment, you will be able to Explain the sampling and analytic procedures
More informationOne-Way Independent ANOVA
One-Way Independent ANOVA Analysis of Variance (ANOVA) is a common and robust statistical test that you can use to compare the mean scores collected from different conditions or groups in an experiment.
More informationHUMAN-COMPUTER INTERACTION EXPERIMENTAL DESIGN
HUMAN-COMPUTER INTERACTION EXPERIMENTAL DESIGN Professor Bilge Mutlu Computer Sciences, Psychology, & Industrial and Systems Engineering University of Wisconsin Madison CS/Psych-770 Human-Computer Interaction
More informationHPS301 Exam Notes- Contents
HPS301 Exam Notes- Contents Week 1 Research Design: What characterises different approaches 1 Experimental Design 1 Key Features 1 Criteria for establishing causality 2 Validity Internal Validity 2 Threats
More informationVALIDITY OF QUANTITATIVE RESEARCH
Validity 1 VALIDITY OF QUANTITATIVE RESEARCH Recall the basic aim of science is to explain natural phenomena. Such explanations are called theories (Kerlinger, 1986, p. 8). Theories have varying degrees
More informationDesigns. February 17, 2010 Pedro Wolf
Designs February 17, 2010 Pedro Wolf Today Sampling Correlational Design Experimental Designs Quasi-experimental Design Mixed Designs Multifactioral Design Sampling Overview Sample- A subset of a population
More informationStill important ideas
Readings: OpenStax - Chapters 1 13 & Appendix D & E (online) Plous Chapters 17 & 18 - Chapter 17: Social Influences - Chapter 18: Group Judgments and Decisions Still important ideas Contrast the measurement
More informationLecture Notes Module 2
Lecture Notes Module 2 Two-group Experimental Designs The goal of most research is to assess a possible causal relation between the response variable and another variable called the independent variable.
More informationExperimental Design Part II
Experimental Design Part II Keith Smolkowski April 30, 2008 Where Are We Now? esearch eview esearch Design: The Plan Internal Validity Statements of Causality External Validity Statements of Generalizability
More informationLevels of Evaluation. Question. Example of Method Does the program. Focus groups with make sense? target population. implemented as intended?
Program Evaluation Jonathan Howland, PhD, MPH 1 Formative Process Level Outcome Levels of Evaluation Question Example of Method Does the program Focus groups with make sense? target population. Was the
More informationLesson 2 The Experimental Method
A Level Psychology Year 1 Research Methods Lesson 2 The Experimental Method Lesson Objectives Describe and evaluate the different types of experiment. Describe, formulate and distinguish between aims and
More informationSociological Research Methods and Techniques Alan S.Berger 1
Sociological Research Methods and Techniques 2010 Alan S.Berger 1 Sociological Research Topics Sociologists: Study the influence that society has on people s attitudes and behavior Seek to understand ways
More informationBIOL 458 BIOMETRY Lab 7 Multi-Factor ANOVA
BIOL 458 BIOMETRY Lab 7 Multi-Factor ANOVA PART 1: Introduction to Factorial ANOVA ingle factor or One - Way Analysis of Variance can be used to test the null hypothesis that k or more treatment or group
More informationLimitations of 2-cond Designs
Limitations of 2-cond Designs Multiple Group Designs Limits of 2 condition designs Kinds of Treatment Conditions Kinds of Control Conditions 2 Kinds of Causal Research Hypotheses 2-cond designs work well
More informationSHARED DECISION MAKING WORKSHOP SMALL GROUP ACTIVITY LUNG CANCER SCREENING ROLE PLAY
SHARED DECISION MAKING WORKSHOP LUNG CANCER SCREENING ROLE PLAY Instructions Your group will role play a Shared Decision Making (SDM) conversation around lung cancer screening using the provided scenario.
More information3 CONCEPTUAL FOUNDATIONS OF STATISTICS
3 CONCEPTUAL FOUNDATIONS OF STATISTICS In this chapter, we examine the conceptual foundations of statistics. The goal is to give you an appreciation and conceptual understanding of some basic statistical
More informationTesting Means. Related-Samples t Test With Confidence Intervals. 6. Compute a related-samples t test and interpret the results.
10 Learning Objectives Testing Means After reading this chapter, you should be able to: Related-Samples t Test With Confidence Intervals 1. Describe two types of research designs used when we select related
More informationAlcohol Consumption Among YSU Students Statistics 3717, CC:2290 Elia Crisucci, Major in Biology Tracy Hitesman. Major in Biology Melissa Phillipson,
Alcohol Consumption Among YSU Students Statistics 3717, CC:2290 Elia Crisucci, Major in Biology Tracy Hitesman. Major in Biology Melissa Phillipson, Major in Biology May 7, 2002 I. Executive Summary: Many
More informationVariables Research involves trying to determine the relationship between two or more variables.
1 2 Research Methodology Week 4 Characteristics of Observations 1. Most important know what is being observed. 2. Assign behaviors to categories. 3. Know how to Measure. 4. Degree of Observer inference.
More informationChapter 4: Defining and Measuring Variables
Chapter 4: Defining and Measuring Variables A. LEARNING OUTCOMES. After studying this chapter students should be able to: Distinguish between qualitative and quantitative, discrete and continuous, and
More informationBetween Groups & Within-Groups ANOVA
Between Groups & Within-Groups ANOVA BG & WG ANOVA Partitioning Variation making F making effect sizes Things that influence F Confounding Inflated within-condition variability Integrating stats & methods
More information2 Critical thinking guidelines
What makes psychological research scientific? Precision How psychologists do research? Skepticism Reliance on empirical evidence Willingness to make risky predictions Openness Precision Begin with a Theory
More informationDisposition. Quantitative Research Methods. Science what it is. Basic assumptions of science. Inductive and deductive logic
Quantitative Research Methods Sofia Ramström Medicinska vetenskaper, Örebro Universitet Diagnostikcentrum, klinisk kemi, Region Östergötland Disposition I. What is science and what is quantitative science?
More informationScience in Natural Resource Management ESRM 304
Science in Natural Resource Management ESRM 304 Science in Natural Resource Management I. The scientific approach to knowledge II. III. Hypothesis testing and resource management Read This! Study Tips
More information