Measurement Chapter 8 Cooper and Schindler Measurement Consist

Measurement Chapter 8 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 threepart 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 ABCDE Desirability of styling to show attendees A-E Gender Empirical Observations of show attendees A-E Assign 5 if Very Desirable 4 if Desirable 3 if neither 1 2 if undesirable 1 if Very Undesirable Mapping Rule Assign “M” if male “F” if female M Symbol ABCDE F (1 through 5) 2 3 4 5

What Is Measured? (I) • Concepts – Objects • Include 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) – 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 – 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

• Validity Sound Measurement – 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

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