What do indexes and scales have in common

Elements are selected from their location, then analyzed for characteristics that would make them good subjects for specific research. Appropriate subjects are then selected according to the data.

Sometimes, such as in medical research, this is desired. Normally, elements are homogenized more in these cases. A typology is the classification of observations in terms of their attributes on two or more variables. Other Important terminology: Correlation : An empirical relationship two variables such that 1. Correlation in and of itself does not constitute a casual relationship between the two variables, but it is one creation of causality.

Spurious Relationship : A coincidental statistical correlation between two variables, shown to be caused by some third variable. Units of Analysis : The what or whom being studied. In social science research, the most typical units of analysis are individual people. Social Artifact : Any product of social beings or their behavior. Can be a unit of analysis. Ecological Fallacy : Erroneously drawing conclusions about individuals solely from the observation of groups.

Reductionism : A fault of some researches: a strict limitation reduction of the kinds of concepts to be considered relevant to the phenomenon under study. Sociobiology : A paradigm based in the view that social behavior can be explained solely in terms of genetic characteristics and behavior Cross-sectional Study : A study based on observation representing a single point in time.

Longitudinal Study : A study design involving the collection of data at different points in time. Trend Study : A type of longitudinal study in which a given characteristic of some population is monitored over time. An example would be the series of Gallup Polls showing the electorate's preferences for political candidates over the course of a campaign, even hough different samples were interviewed at each point.

Cohort Study : A study in which some specific subpopulation, or cohort, is studied over time, although data may be collected from different members in each set of observations.

For example, a study of the questionnaires were sent every five years would be a cohort study. Panel Study : A type of longitudinal study, in which data are collected from the same set of people the sample or panel at several points in time.

Index Construction Item Selection Face validity or logical validity Unidimensional--a composite measure should represent only one dimension of a concept. General or Specific--the nature of the items you include will determine specifically or generally the variable that is measured. Variance--to guarantee variance you can a select several items the responses to which divide people about equally in terms of the variable b select items differing in variance Examination of Empirical Relationships Bivariate relationship: a relationship between two variables.

Multivariate relationship: a relationship between two or more variables. Index Scoring Determine the desirable range of index scores Determine whether to give each item in the index equal or different weights Make sure to standardize the weights--items should be weighted equally unless there are reasons not to.

Handling Missing Data You may decide to exclude them from the construction of the index and analyses Treat missing data as one of the available responses Analyze missing data and interpret their meaning Assign missing data a middle value or mean value Assign values to the proportion of the variables scored. Index Validation Item analysis an assessment of whether each of the items included in the measure makes an independent contribution or merely duplicates the contribution of other items in the measure External validation tests the validity by examining its relationship to other presumed indicators of the same variable.

A person who answers YES to every question is as liberal as you can get. A person who says YES to none of them is not at all liberal. The individual questions used in this way are known as items. The collection of questions is called a scale. The term scale also refers to the actual total scores obtained by each respondent its confusing, I know! All scales are indices, but not all indexes are scales. An index really just means that it is a measurement that is constructed by summing up other, simpler, measurements.

A scale is an index that in some sense only measures one thing. For example, a final exam in a given course could be thought of as a scale: it measures competence in a single subject. In contrast, a person's gpa can be thought of as an index: it is a combination of a number of separate, independent competencies.

Cohort Study : A study in which some specific subpopulation, or cohort, is studied over time, although data may be collected from different members in each set of observations. For example, a study of the questionnaires were sent every five years would be a cohort study.

Panel Study : A type of longitudinal study, in which data are collected from the same set of people the sample or panel at several points in time. From Wikibooks, open books for an open world. Indices, Scales and Typologies Quantitative data analysis requires the construction of two types of measures of variables--indices and scales.

Index Construction [ edit edit source ] Item Selection Face validity or logical validity Unidimensional--a composite measure should represent only one dimension of a concept. General or Specific--the nature of the items you include will determine specifically or generally the variable that is measured. Variance--to guarantee variance you can a select several items the responses to which divide people about equally in terms of the variable b select items differing in variance Examination of Empirical Relationships Bivariate relationship: a relationship between two variables.

Multivariate relationship: a relationship between two or more variables. Index Scoring Determine the desirable range of index scores Determine whether to give each item in the index equal or different weights Make sure to standardize the weights--items should be weighted equally unless there are reasons not to.

Handling Missing Data You may decide to exclude them from the construction of the index and analyses Treat missing data as one of the available responses Analyze missing data and interpret their meaning Assign missing data a middle value or mean value Assign values to the proportion of the variables scored. Index Validation Item analysis an assessment of whether each of the items included in the measure makes an independent contribution or merely duplicates the contribution of other items in the measure External validation tests the validity by examining its relationship to other presumed indicators of the same variable.

A scale is a measure of the intensity of an attitude or emotion. Specifically, scales exist in the ordinal level of data. Usually scales are constructed using the ordinal level of measurement, which organizes items in an order in order to determine degrees of favor or disfavor, but does not provide any meaning of distance between degrees.

The Likert scale is one of the most commonly used scales in the research community. The scale consists of assigning a numerical value to intensity or neutrality of emotion about a specific topic, and then attempts to standardize these response categories to provide an interpretation of the relative intensity of items on the scale. The semantic differential scale is similar to Likert scaling, however, rather than allowing varying degrees of response, it asks the respondent to rate something in terms of only two completely opposite adjectives.

An example of a scale used in real-life situations is the Bogardus Social Distance Scale. Thurstone scaling is quite unlike Bogardus or Likert scaling. Developed by Louis Thurstone, this scale is a format that seeks to use respondents both to answer survey questions, and to determine the importance of the questions.

Guttman scaling, like the Thurstone scale, recognizes that different questions provide different intensities of indication of preferences. It is based upon the assumption that the agreement with the strongest indicators also signifies agreement with weaker indicators. There are two misconceptions of scaling, one of which is the combination of data into a scale is influenced by the observation of the sample of the study.

Thus the data of one scale from a sample may not comply with another scale. Therefore that combination of data can be scaled multiple times because it was originally was able to earlier in the study. A second misconception pertains to specific scales. By this, given items or data may aid in determine what constitutes as a scale opposed to a scale itself.

Scales versus Indices In general, scales are considered to function better than indexes, due to the fact that scales usually consider intensity of the questions they ask and feelings they measure, despite the fact that both are ordinal measures.

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