Chapter 6 Indexes Scales and Typologies The terms

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Chapter 6 Indexes, Scales, and Typologies

Chapter 6 Indexes, Scales, and Typologies

The terms index and scale are typically used imprecisely and interchangeably in social research

The terms index and scale are typically used imprecisely and interchangeably in social research literature.

Ø Both scale and indexes are ordinal measures of variables. Ø Both rank-order the

Ø Both scale and indexes are ordinal measures of variables. Ø Both rank-order the units of analysis in terms of specific variables such as religiosity, alienation, socioeconomic status, prejudice.

Ø Both scales and indexes are composite measures of variables – that is, measurements

Ø Both scales and indexes are composite measures of variables – that is, measurements based on more than one data item.

Ø Eg. A survey respondent’s score on an index or scale of religiosity is

Ø Eg. A survey respondent’s score on an index or scale of religiosity is determined by the response given to several questionnaire items, each of which provides some indication of religiosity

Index Ø An index is constructed by simply accumulating scores assigned to individual attributes.

Index Ø An index is constructed by simply accumulating scores assigned to individual attributes. We might measure prejudice, for example, by adding up the number of prejudiced statements each respondent agreed with

Scale A scale is constructed by assigning scores to patterns of responses, recognizing that

Scale A scale is constructed by assigning scores to patterns of responses, recognizing that some items reflect a relatively weak degree of the variable while others reflect something stronger Ø Scales are generally superior to indexes, because scales take into consideration the intensity with which different items reflect the variable being measured Ø Scale scores convey more information than index scores Ø

Index Construction Ø Selecting possible items Ø Examining their empirical relationships Ø Scoring the

Index Construction Ø Selecting possible items Ø Examining their empirical relationships Ø Scoring the index Ø Validating it

Item Selection Face validity Ø the first criterion for selecting items to be included

Item Selection Face validity Ø the first criterion for selecting items to be included in the index is face validity (or logical validity). Ø if you want to measure political conservatism, for example, each of your items should appear on its face to indicate conservatism

Item Selection Unidimensionality Ø the methodological literature on conceptualization and measurement stresses the need

Item Selection Unidimensionality Ø the methodological literature on conceptualization and measurement stresses the need for unidimensionality in scale and indexes construction Ø a composite measure should represent only one dimension of a concept

Item Selection General or Specific Ø the general dimension you’re attempting to measure may

Item Selection General or Specific Ø the general dimension you’re attempting to measure may have many nuances Ø in the example of religiosity, the indicators – ritual participation, belief – represent different types of religiosity

Item Selection Variance the amount of variance that is provided by items Ø to

Item Selection Variance the amount of variance that is provided by items Ø to have variance, you have two options Ø first – you may select several items the responses to which divide people about equally in terms of the variable Ø second- select items differing in variance – one item might identify about half the subjects as conservative, while another might identify few of the respondents as conservatives Ø

Examining of Empirical Relationships Ø Response to one question will help us predict how

Examining of Empirical Relationships Ø Response to one question will help us predict how that respondent will answer on other questions Ø Bivariate relationships Ø Multivariate relationships

Index Scoring Ø Decide the range of index scores Ø See how many cases,

Index Scoring Ø Decide the range of index scores Ø See how many cases, questions, for each point in the scale Ø Assigning scores for each particular response – usually weighted equally unless there is a reason for heavier weight for a case

Handling Missing Data Ø Exclude the cases Ø Treat it as one of the

Handling Missing Data Ø Exclude the cases Ø Treat it as one of the existing responses Ø Don’t know answers Ø Assign middle value Ø proportions

Index Validation Item analysis (internal validation) – you examine the extent to which the

Index Validation Item analysis (internal validation) – you examine the extent to which the index is related to (or predicts responses to) the individual items it comprises Ø if the index adequately measures a given variable, it should successfully predict other indications of that variable Ø External validation – people scored as politically conservative on an index should appear conservative by other measures as well, such as their responses to other items in the questionnaire Ø

Scale Construction Ø Scales offer more assurance of ordinality by tapping the intensity structures

Scale Construction Ø Scales offer more assurance of ordinality by tapping the intensity structures among the indicators

Bogardus Social Distance Scale is a measurement technique for determining the willingness of people

Bogardus Social Distance Scale is a measurement technique for determining the willingness of people to participate in social relations – of varying degrees of closeness – with other kinds of people Ø if a person is willing to accept a given kind of association, he or she would be willing to accept all those preceding it in the list – those with lesser intensities Ø more people agree to the easy items than to the hard ones Ø logic demands that once a person has refused a relationship presented in the scale, he or she will also refuse all the harder ones that follow it Ø

Thurstone Scales an attempt to develop a format for generating groups of indicators of

Thurstone Scales an attempt to develop a format for generating groups of indicators of a variable that have at least an empirical structure among them Ø each judge is asked to estimate how strong an indicator of a variable each item is by assigning scores of perhaps 1 -13 Ø once the judges have completed this task, the researcher examines the scores assigned to each item by all the judges to determine which items produced the greatest agreement among the judges Ø

Likert Scale Ø - contains responses strongly agree, disagree, and strongly disagree

Likert Scale Ø - contains responses strongly agree, disagree, and strongly disagree

Semantic Differential Ø asks questionnaire respondents to choose between two opposite positions using qualifiers

Semantic Differential Ø asks questionnaire respondents to choose between two opposite positions using qualifiers to bridge the gap between the two opposites Ø you need to find two opposite terms, representing the polar extremes along each dimensions

Semantic Differential Example Feelings about musical selections: ___________________________________ Very much somewhat neither somewhat very

Semantic Differential Example Feelings about musical selections: ___________________________________ Very much somewhat neither somewhat very much ___________________________________ simple complex enjoyable unenjoyable traditional modern

Guttman Scale based on the fact that some items under consideration may prove to

Guttman Scale based on the fact that some items under consideration may prove to be more extreme indicators of the variable than others Ø begin by examining the face validity of items available for analysis – then you would examine the bivariate and perhaps multivariate relations among those items Ø also look at hard and easy indicators of the variable being examined Ø based on the notion that anyone who gives a strong indicator of some variable will also give the weaker indicators Ø

Typology Ø Summarize the intersection of two or more concepts or variables, creating a

Typology Ø Summarize the intersection of two or more concepts or variables, creating a category or type – nominal variable