Download presentation
Presentation is loading. Please wait.
Published byEmerald Jenkins Modified over 8 years ago
1
© 2009 Pearson Prentice Hall, Salkind. Chapter 5 Measurement, Reliability and Validity
2
© 2009 Pearson Prentice Hall, Salkind. CHAPTER OBJECTIVES STUDENTS SHOULD BE ABLE TO: Explain why measurement is important to the research process. Discuss the four levels of measurement and provide an example of each. Explain the concept of reliability in terms of observed score, true score, and error. Describe the two elements that can make up an error score. List methods for increasing reliability. Discuss four ways in which reliability can be examined. Provide a conceptual definition of validity. List the three traditional types of validity. Explain the relationship between reliability and validity.
3
© 2009 Pearson Prentice Hall, Salkind. CHAPTER OVERVIEW The Measurement Process Levels of Measurement Reliability and Validity: Why They Are Very, Very Important Validity The Relationship Between Reliability and Validity Closing (and Very Important) Thoughts
4
© 2009 Pearson Prentice Hall, Salkind. THE MEASUREMENT PROCESS
5
© 2009 Pearson Prentice Hall, Salkind. THE MEASUREMENT PROCESS Two definitions Stevens—“assignment of numerals to objects or events according to rules.” “…the assignment of values to outcomes.” Chapter foci Levels of measurement Reliability and validity
6
© 2009 Pearson Prentice Hall, Salkind. LEVELS OF MEASUREMENT Variables are measured at one of these four levels Qualities of one level are characteristic of the next level up The more precise (higher) the level of measurement, the more accurate is the measurement process Level of Measurement For ExampleQuality of Level Ratio Rachael is 5 ’ 10 ” and Gregory is 5 ’ 5 ” Absolute zero Interval Rachael is 5 ” taller than Gregory An inch is an inch is an inch OrdinalRachael is taller than GregoryGreater than NominalRachael is tall and Gregory is shortDifferent from
7
© 2009 Pearson Prentice Hall, Salkind. NOMINAL SCALE QualitiesExampleWhat You Can Say What You Can’t Say Assignment of labels Gender— (male or female) Preference— (like or dislike) Voting record— (for or against) Each observation belongs in its own category An observation represents “more” or “less” than another observation
8
© 2009 Pearson Prentice Hall, Salkind. ORDINAL SCALE QualitiesExampleWhat You Can Say What You Can’t Say Assignment of values along some underlying dimension Rank in college Order of finishing a race One observation is ranked above or below another. The amount that one variable is more or less than another
9
© 2009 Pearson Prentice Hall, Salkind. INTERVAL SCALE QualitiesExampleWhat You Can Say What You Can’t Say Equal distances between points Number of words spelled correctly Intelligence test scores Temperature One score differs from another on some measure that has equally appearing intervals The amount of difference is an exact representation of differences of the variable being studied
10
© 2009 Pearson Prentice Hall, Salkind. RATIO SCALE QualitiesExampleWhat You Can Say What You Can’t Say Meaningful and non-arbitrary zero Age Weight Time One value is twice as much as another or no quantity of that variable can exist Not much!
11
© 2009 Pearson Prentice Hall, Salkind. CONTINUOUS VERSUS DISCRETE VARIABLES Continuous variables Values can range along a continuum E.g., height Discrete variables (categorical) Values are defined by category boundaries E.g., gender
12
© 2009 Pearson Prentice Hall, Salkind. WHAT IS ALL THE FUSS? Measurement should be as precise as possible In psychology, most variables are probably measured at the nominal or ordinal level But—how a variable is measured can determine the level of precision
13
© 2009 Pearson Prentice Hall, Salkind. RELIABILITY AND VALIDITY: WHY THEY ARE VERY, VERY IMPORTANT
14
© 2009 Pearson Prentice Hall, Salkind. RELIABILITY AND VALIDITY Reliability—tool is consistent Validity—tool measures “what-it-should” Good assessment tools Rejection of Null hypotheses OR Acceptance of Research hypotheses
15
© 2009 Pearson Prentice Hall, Salkind. A CONCEPTUAL DEFINITION OF RELIABILITY Method Error Observed Score = True Score + Error Score Trait Error
16
© 2009 Pearson Prentice Hall, Salkind. A CONCEPTUAL DEFINITION OF RELIABILITY Observed score Score actually observed Consists of two components True Score Error Score Method Error Observed Score = True Score + Error Score Trait Error
17
© 2009 Pearson Prentice Hall, Salkind. A CONCEPTUAL DEFINITION OF RELIABILITY True score Perfect reflection of true value for individual Theoretical score Method Error Observed Score = True Score + Error Score Trait Error
18
© 2009 Pearson Prentice Hall, Salkind. Error score Difference between observed and true score Method Error Observed Score = True Score + Error Score Trait Error A CONCEPTUAL DEFINITION OF RELIABILITY
19
© 2009 Pearson Prentice Hall, Salkind. Method error is due to characteristics of the test or testing situation Trait error is due to individual characteristics Conceptually, reliability = Reliability of the observed score becomes higher if error is reduced!! Method Error Observed Score = True Score + Error Score Trait Error True Score True Score + Error Score A CONCEPTUAL DEFINITION OF RELIABILITY
20
© 2009 Pearson Prentice Hall, Salkind. INCREASING RELIABILITY Decreasing Error Increase sample size Eliminate unclear questions Standardize testing conditions Moderate the degree of difficulty of the tests Minimize the effects of external events Standardize instructions Maintain consistent scoring procedures
21
© 2009 Pearson Prentice Hall, Salkind. HOW RELIABILITY IS MEASURED Reliability is measured using a Correlation coefficient r test1test2 Reliability coefficients Indicate how scores on one test change relative to scores on a second test Can range from -1.0 to +1.0 +1.00 = perfect reliability 0.00 = no reliability
22
© 2009 Pearson Prentice Hall, Salkind. TYPES OF RELIABILITY Type of Reliability What It IsHow You Do ItWhat the Reliability Coefficient Looks Like Test-RetestA measure of stability Administer the same test/measure at two different times to the same group of participants r test1test1 Parallel Forms A measure of equivalence Administer two different forms of the same test to the same group of participants r form1form2 Inter-RaterA measure of agreement Have two raters rate behaviors and then determine the amount of agreement between them Percentage of agreements Internal Consistency A measure of how consistently each item measures the same underlying construct Correlate performance on each item with overall performance across participants Cronbach’s alpha Kuder-Richardson
23
© 2009 Pearson Prentice Hall, Salkind. VALIDITY
24
© 2009 Pearson Prentice Hall, Salkind. VALIDITY A valid test does what it was designed to do A valid test measures what it was designed to measure
25
© 2009 Pearson Prentice Hall, Salkind. A CONCEPTUAL DEFINITION OF VALIDITY Validity refers to the test’s results, not to the test itself Validity ranges from low to high, it is not “either/or” Validity must be interpreted within the testing context
26
© 2009 Pearson Prentice Hall, Salkind. TYPES OF VALIDITY Type of ValidityWhat Is It?How Do You Establish It? ContentA measure of how well the items represent the entire universe of items Ask an expert if the items assess what you want them to Criterion ConcurrentA measure of how well a test estimates a criterion Select a criterion and correlate scores on the test with scores on the criterion in the present PredictiveA measure of how well a test predicts a criterion Select a criterion and correlate scores on the test with scores on the criterion in the future ConstructA measure of how well a test assesses some underlying construct Assess the underlying construct on which the test is based and correlate these scores with the test scores
27
© 2009 Pearson Prentice Hall, Salkind. HOW TO ESTABLISH CONSTRUCT VALIDITY OF A NEW TEST Correlate new test with an established test Show that people with and without certain traits score differently Determine whether tasks required on test are consistent with theory guiding test development
28
© 2009 Pearson Prentice Hall, Salkind. MULTITRAIT-MULTIMETHOD MATRIX Convergent validity—different methods yield similar results Discriminant validity—different methods yield different results Method 1 Paper and Pencil Method 2 Activity Level Monitor Method 1 Paper and Pencil Method 2 Activity Level Monitor Trait 1 Method 1 Paper and Pencil ModerateLow Impulsivity Method 2 Activity Level Monitor Moderate Trait 2 Method 1 Paper and Pencil Activity Level Method 2 Activity Level Monitor Low Trait 1 Impulsivity Trait 2 Activity Level
29
© 2009 Pearson Prentice Hall, Salkind. THE RELATIONSHIP BETWEEN RELIABILITY AND VALIDITY
30
© 2009 Pearson Prentice Hall, Salkind. THE RELATIONSHIP BETWEEN RELIABILITY AND VALIDITY A valid test must be reliable But A reliable test need not be valid
31
© 2009 Pearson Prentice Hall, Salkind. CLOSING (AND VERY IMPORTANT) THOUGHTS
32
© 2009 Pearson Prentice Hall, Salkind. CLOSING (AND VERY IMPORTANT) THOUGHTS You must define a reliable and valid dependent variable or you will not know whether or not there truly is no difference between groups! Use a test with established and acceptable levels of reliability and validity. If you cannot do this, develop such a test for your thesis or dissertation (and do no more than that) OR change what you are measuring.
33
© 2009 Pearson Prentice Hall, Salkind. HAVE WE MET THE OBJECTIVES? CAN YOU: Explain why measurement is important to the research process? Discuss the four levels of measurement and provide an example of each? Explain the concept of reliability in terms of observed score, true score, and error? Describe the two elements that can make up an error score? List methods for increasing reliability? Discuss four ways in which reliability can be examined? Provide a conceptual definition of validity? List the three traditional types of validity? Explain the relationship between reliability and validity?
Similar presentations
© 2024 SlidePlayer.com. Inc.
All rights reserved.