Measurement Concepts and scale evaluation

Contents Identifying and deciding on the variables to be measured Development of measurement scales Types of measurement scales Scale evaluation

The process of assigning numbers or labels to different objects under study to represent them quantitatively or qualitatively is called measurement . Scaling involves the generation of continuum on which measured objects are located.

Identifying and deciding on the variables to be measured The primary step in the measurement process is to identify the area or the concept that is of interest for the study. While conducting business research, a researcher has to initially define what is to be measured, how it will be measured, and also the concept that needs to be measured.

Development of measurement scales A scale can be defined as a set of numbers or symbols developed in a manner so as to facilitate the assignment of these numbers or symbols to the units under research following certain rules.

Measurement scales The design of a measurement scale depends on the objective of the research study, and the mathematical or statistical calculations that a researcher expects to perform on the data collected using the scales. Types of Measurement scales are as follows: Nominal scales Ordinal scales Interval scales Ratio scale

Scale evaluation A multiitem scale should be evaluated for accuracy and applicability. This involves assessment of reliabilty,validity and generalizabilty of the scale. Measurement accuracy can be depicted by a true score model as below Xo=Xt +Xs+Xr Where, Xo=observed score or measurement Xt=true score of characteristic Xs=Systematic error Xr=random error

Scale evaluation Reliability Validity Reliability Test-retest Internal consistency Equivalent form reliability Construct validity Face validity Content validity Criterion-related validity

Scale evaluation contd…. Reliability It refers to the extent to which a scale produces consistent results if measurements are made repeatedly. Test-retest reliability: The respondents are administered identical sets of scale items at two different times in nearly equivalent conditions as possible. Alternative forms reliability: two equivalent forms of the scale are constructed Internal consistency reliability is used to assess the reliability of a summated scale in which several items are summed to form a total score. In split half reliability items of scale are divided into two equal halves and resulting half scores are correlated.

Scale evaluation contd…. Validity of a scale may be defined as the extent to which differences in observed scores reflect true differences among objects on the characteristic being measured ie Xo=Xt Content validity is systematic evaluation of how well the content of a scale represents the measurement task, whether the scale items cover the entire domain of the construct being measured.

Scale evaluation contd…. Criterion validity reflects whether a scale performs as expected in relation to other variables selected as meaningful criterion. It has two forms: Concurrent validity is assessed when data on the scale being evaluated and on the criterion variables are collected at the same time. Predictive validity is assessed when data on the scale is collected at one point of time and data on criterion variables at a future time

Construct validity It aims to first define the concept/construct explicitly and then to show that measurement or operational definition logically connects the empirical phenomenon with the construct with the construct. Two basic types are: Convergent validity is the extent to which the scale correlates positively with other measures of the same construct. Discriminant validity is the extent to which a measure does not correlate with other constructs from which it is supposed to differ.

Sensitivity: Generalizability: Relevance: It refers to an instrument’s ability to accurately measure variability in stimuli or responses. Sensitivity is not high in instrument’s involving ‘Agree’ or ‘Disagree’ types of response. Generalizability: It refers to the amount of flexibility in interpreting the data in different research designs. Relevance: It refers to the appropriateness of using a particular scale for measuring a variable. Relevance = reliability x validity

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