# 9-1 Chapter Nine MEASUREMENT SCALES. 9-2 Scaling and Consideration What is Scaling? –Scaling is assigning numbers to indicants of the properties of objects.

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9-1 Chapter Nine MEASUREMENT SCALES

9-2 Scaling and Consideration What is Scaling? –Scaling is assigning numbers to indicants of the properties of objects Consideration in Scale Selection –Study objective: Which objective to measure? Characteristics of the participants Attitude or opinion of the participants –Response form: Which scale to use? Rating scale, Ranking scale or category

9-3 Scaling and Consideration Continued –Degree of preference: Which one to measure? Preference or non-preference –What is the data property? Nominal, ordinal, interval, or ratio data –Number of dimension? Uni-dimensional or multi-dimensional –How to develop scales? Arbitrary, consensus, item analysis, cumulative scaling or factor analysis

9-4 Types of Rating Scales Simple category (dichotomous scale) Multiple choice, single response Multiple choice, multiple response (check list) Likert scale (a variant of summated rating scale) Semantic differential

9-5 Types of Rating Scales Continued Numerical scale Fixed sum: to find proportions Stapel scale (alternative to semantic differential) Graphic rating (often used with children) –Advantage –Disadvantage

9-6 Rating Scale Errors to Avoid Leniency –Negative Leniency –Positive Leniency Central Tendency Halo Effect: the systematic bias by the rater from carrying over a generalized impression of the subject from one rating to another.

9-7 Types of Ranking Scales Paired-comparison: choosing between two objects Forced Ranking Comparative Scale: standard to compare is provided

9-8 Dimensions of a Scale Unidimensional: measuring only one attribute of the participant or object Multidimensional: measuring several attributes (or aspects) of the participant or object

9-9 Scale Design Techniques (Measurement Scale Construction) Arbitrary scaling -subjective Consensus scaling - costly Item Analysis scaling (statistical analysis of each item, using t-test) Cumulative scaling (analysis of scalogram) Factor analysis (in Chapter 19)

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