Measurement Foundations PDF

MEASUREMENT FOUNDATIONS Learning Objectives After reading this chapter, you should understand…. The distinction among measuring objects, properties, and indicants of properties. The similarities and diff erences among the four scale types used in measurement and when each is used...

MEASUREMENT FOUNDATIONS Learning Objectives After reading this chapter, you should understand…. The distinction among measuring objects, properties, and indicants of properties. The similarities and diff erences among the four scale types used in measurement and when each is used. The four major sources of measurement error. The criteria for evaluating good measurement. The Nature of Measurement To measure is to discover the extent, dimensions, quantity, or capacity of something, especially by comparison with a standard. The goal of measurement is to provide the highest-quality, lowest-error data for testing hypotheses, forming estimates or predictions, or describing. Tasks of Measurement Thus, measurement in research consists of assigning numbers to empirical events, objects, or properties, or activities in compliance with a set of rules. This definition implies that measurement has three tasks: 1.Select variables to measure. 2.Develop a set of mapping rules: a scheme for assigning numbers or symbols to represent aspects of variable being measured. 3.Apply the mapping rule(s) to each observation of that event. What Is Measured? Variables measured in research may be classifi ed as objects or as properties. Objects include both concepts and constructs. Concepts are the more concrete and tangible items of daily life, like furniture, laundry detergent, a person, or an automobile. Constructs are more abstract, like peer pressure, leadership, or lifestyle. Properties are the characteristics of an object. Measurement Scales A study’s quality depends on what measures are selected or developed and how they fi t the circumstances. In measuring, one devises some mapping rule and then translates the observation of property indicants using this rule. Given the nature of the object or property, mapping rules follow one of four assumptions: 1. Numerical labels are used to classify, group, or sort responses. No order exists because the numbers have no arithmetic value. 2. Numerical labels provide order. One number is greater than, less than, or equal to another number. 3. Numerical labels provide order and the diff erences between numbers is greater than, less than, or equal to the diff erence between any other pair of numbers. 4. Numerical labels have arithmetic value because the numbers series has a unique origin indicated by the number Combinations of these characteristics of classifi cation, order, distance, and origin provide four widely used classifi cations of measurement scales. (1) Nominal Scales- In business research, nominal data are widely used. With nominal scales, you are collecting information on a variable that naturally or by design can be grouped into two or more categories that are mutually exclusive and collectively exhaustive. (2) Ordinal Scales- Ordinal scales include the characteristics of the nominal scale plus an indication of order. Ordinal data require conformity to a logical premise, which states: If a is greater than b and b is greater than c, then a is greater than c. The use of an ordinal scale implies a statement of “greater than” or “less than” or “equal to”. (3) Interval Scales- Interval scales have the power of nominal and ordinal data plus one additional strength: They incorporate the concept of equality of interval. Calendar time is such a scale. (4) Ratio Scales- Ratio scales incorporate all of the powers of the previous scales plus the provision for absolute zero or  Error Sources The Participant Situational The The Factors Measurer Instrument Opinion diff erences Any condition that The interview A defective that aff ect places a strain on measurement can distort measurement come the interview or instrument can cause from relatively stable responses by distortion in two major measurement characteristics of the rewording, ways. First, it can be session can have participant. Typical of paraphrasing, or too confusing and serious eff ects on these are employee reordering ambiguous. And a the interviewers- status, ethnic group more elusive type of participant rapport. questions. membership, social instrument defi ciency class, and nearness to is one that doesn’t manufacturing cover the facilities. investigative questions. The Characteristics of Good Measurement There are three major criteria for evaluating a measurement tool: Validity- is the extent to which a chosen or developed scale actually measure what we 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 in measurement. VALIDITY Many forms of validity are mentioned in the research literature. One widely accepted classifi cation of internal validity consists of three major forms: 1.Content Validity- The content validity of a measuring instruments is the extent to which it provides adequate coverage of the investigative questions guiding the study. 2. Criterion-Related Validity- Criterion- related validity refl ects the success of measures used for prediction or estimation. You may want to predict an outcome or estimate the existence of a current behavior or time perspective. The researcher must ensure that the validity criterion used is itself “valid”. Any criterion measure must be judged in terms of four qualities: (1) Relevance- A criterion is relevant if it is defi ned and scored in the terms we judge to be the proper measures of salesperson success. (2) Freedom from bias- is attained when the criterion gives each salesperson an equal opportunity to score well. (3) Reliability- A reliable criterion is stable or reproducible. (4) Availability- for a criterion to be available the data must be accessible. 3. Construct Validity- In attempting to evaluate construct validity, we consider both the theory and the measurement instrument being used. The three forms of validity are interrelated, both theoretically and operationally. Predictive validity is important for a measurement designed to predict product success.  Stability- A measure is said to possess stability if you can secure consistent results with repeated measurements of the same person with the same RELIABILITY instrument. An observation procedure is stable if it gives the same reading on a particular person when repeated one or more times. Equivalence- A second perspective on reliability considers how much error may be introduced by Reliability is concerned with the diff erent investigators (in observation) or diff erent degree to which a measurement measurement questions being studied (in surveys). Thus, while stability is concerned with personal and is free of random or unstable situational fl uctuations from one time to another, equivalence is concerned with variations at one point in error. A measure is reliable to time among observers and measurement questions. the degree that it supplies Internal Consistency- A third approach to reliability consistent results. uses only one administration of an instrument to assess the internal consistency or homogeneity among the items or measurement questions. The split-half technique can be used when the measurement instrument has many similar questions or statements to which the participant can respond.  Economy- Some trade-off usually occurs between the ideal research project and the PRACTICALITY budget. Data are not free, and instrument length is one area where economic pressures dominate. Convenience- A measurement instrument Practicality has been defi ned as passes the convenience test if it is easy to administer. A questionnaire or a measurement having economy, convenience, instrument with a set of detailed but clear and interpretability. instructions, with examples, is easier to complete correctly than one that lacks these features. Interpretability- This aspect of practicality is relevant when persons other than the instrument designer must interpret the results. It is usually, but not exclusively, an issue with standardized measurements. Thank you !