Chapter 7 Cooper and Schindler Measurement Chapter 7 Cooper and Schindler

Measurement Consist of assigning numbers to empirical events in compliance with a set of rules The definition implies that measurement is a three-part process Selecting observable empirical events Using numbers or symbols to represent aspects of the events Applying a mapping rule to connect the observation to the symbol Example Studying people who attend an auto show where all of the year’s new models are on display Gender Styling characteristics

Characteristics of Measurement Gender Styling Characteristics A B C D E A B C D E Desirability of styling to show attendees A-E Empirical Observations Gender of show attendees A-E Assign 5 if Very Desirable 4 if Desirable 3 if neither 2 if undesirable 1 if Very Undesirable Mapping Rule Assign “M” if male “F” if female 1 2 4 3 5 M F (1 through 5) Symbol

What Is Measured? (I) Concepts Objects Include the things of ordinary experience, such as tables, people, books and automobiles Also include things that are not as concrete, such as genes, attitudes, neutrons and peer-group pressures Properties Are the characteristics of the objects Physical properties Psychological properties Social properties Researchers measure indicants of the properties of objects

What Is Measured? (II) It is not easy to measure properties Age, Years of experience, Number of calls per week It is not easy to measure properties Motivation to succeed, ability to stand stress, problem-solving ability, and persuasiveness There is often disagreement about how to operationalize the indicants Not only is it a challenge to measure such constructs, but a study’s quality depends on what measures are selected or constructed, and how they fit the circumstances

Scale Classifications Employ the real numbers systems The most accepted basis for scaling has three characteristics Number are ordered (Order) Differences between numbers are ordered (Distance) The number series has a unique origin indicated by the number zero (Origin)

Measurement Scales Nominal Ordinal Interval Ratio No order, or origin Determination of equality Ordinal Order but no distance or unique origin Determination of greater or lesser values Interval Both order and distance but no unique origin Determination of equality of intervals or differences Ratio Order, distance, and unique origin Determination of equality of ratios

Nominal Scales Partition a set into categories that are mutually exclusive and collectively exhaustive Counting is the only arithmetic operation Only labels and have no quantitative value No order or distance relationship and have no arithmetic origin No general used measure of dispersion Several tests for statistical significance may be utilized Chi-square test For measures of association, phi, lambda, or other measure may be appropriate

Ordinal Scales Include the characteristics of the nominal scale plus an indicator of order Ordinal scales are possible if the transitivity postulate is fulfilled. An extension of the ordinal concept occurs when more than one property is of interest Add and average ranks is technically incorrect Use a multidimensional scale Have another difficulty when combining the rankings of several respondents Convert the ordinal scale into an interval scale Thurstone’s Law of Comparative Judgment

Ordinal Scales Examples of ordinal scales include opinion and preference scales Paired -comparison techniques Ordinal scales have only a rank meaning Statistical measures Central tendency median Dispersion Percentile or quartile Correlation Rank-order methods Statistical significance Nonparametric methods

Interval Scales Has the powers of nominal and ordinal plus one additional strength Incorporates the concept of equality of interval Calendar time is interval scales Zero time and zero degree(Centigrade and Fahrenheit) are arbitrary origin Many attitude scales are presumed to be interval Thurstone’s differential scale was an early effort to develop such a scale Statistical measures Central tendency (Arithmetic mean) Dispersion (Standard deviation) others (Product moment correlation, t-tests, and F-tests)

Ratio Scales Incorporate all of the powers of the previous ones plus the provision for absolute zero or origin Represent the actual amounts of a variable Examples are weight, height, distance, and area In behavioral sciences, few situations satisfy the requirement of the ratio scale(Psychophysics offering some exceptions) In business research, we find ratio scale in many areas (money values, population counts, distances) Statistical measures All statistical mentioned up to this point Multiplication and division Geometric mean, coefficients of variation

Sources of Measurement Differences The respondent as an error source Situation factors The measurer as an error source Instrument as an error source

Sound Measurement Validity Reliability Practicality Content validity Criterion-related validity (Concurrent validity, Predictive validity) Construct validity Reliability Stability (Test-retest) Equivalence (Parallel forms) Internal consistency (Split-half, KR-20, Cronbach’s alpha) Practicality Economy Convenience Interpretability

Criteria for Evaluating a Measurement Tool Validity Refer to the extent to which a test measures what we actually wish to measure Reliability Has to do with the accuracy and precision of a measurement procedure Practicality Is concerned with a wide range of factors of economy, convenience, and interpretability

Validity Internal and external Research Instrument internal validity Measure what it is purported to measure Does the instrument really measure what its designer claims it does? Three major forms Content validity Criterion-related validity Concurrent validity Predictive validity Construct validity

Content Validity The extent to which it provides adequate coverage of the topic under study Determination of content validity is judgmental and can be approached in several ways Through a careful definition of the topic Use a panel of persons to judge

Criteria-Related Validity reflects the success of measures used for prediction or estimation Predict an outcome Estimate the existence of a current behavior or condition Predictive and concurrent validity differ in time perspective An opinion questionnaire that correctly forecasts the outcome of a union election has predictive validity An observational methods that correctly categorizes families by current income class has concurrent validity Any criteria measure must be judged in terms of four qualities: relevance, freedom from bias, reliability, availability

Construct Validity One may wish to measure or infer the presence of abstract characteristics for which no empirical validation seems possible Attitude scales Aptitude tests Personality tests Example Measuring the effects of ceremony on organizational culture Ceremony was operationally defined would have to correspond to an empirically grounded theory Convergent validity Discriminant validity

Reliability A measure is reliable to the degree that it supplies consistent results Reliability is a contributor to validity and is a necessary but not sufficient condition for validity Reliability is concerned with estimates of the degree to which a measurement is free of random or unstable error

Stability A measure is said to be stable if you can secure consistent results with repeated measurements of the same person with the same instrument Test-retest

Equivalence Considers how much error may be introduced by different investigators (in observation) or different samples of items being studied (in questioning or scales) Equivalence is concerned with variations at one point in time among observers and samples of items Interrater reliability may be used to correlate the observations or scores of the judges and render an index of how consistent their ratings are

Internal Consistency Use only one administration of an instrument or test to assess consistency or homogeneity among the items Split-half techniques Spearman-Brown correction formula The test splitting may influence the internal consistency coefficient Kuder-Richardson Formula 20 Cronbach’s Coefficient Alpha