Lesson #7_Level of Measurement_Quantitative Research

level of measurement

1. refers to the way that a variable is measured. Assignment of a value or symbol to represent each observation

2. Va r i ab le is a characteristic, number, or quantity that increases or decreases over time, or takes different values in different situations.

3. 1. Independent variable : that can take different values and can cause corresponding changes in other variables. 2 Dependent variable : that can take different values only in response to an independent variable.

4. Nominal Level Ordinal Level Interval Level Ratio Level

5. At this level, variables simply name the attribute it is measuring and no ranking is present.  Example: Gender – Male and Female  often called qualitative variables Identifies variables whose values have no mathematical interpretation

6.  An important feature of nominal variables is that there is no hierarchy or ranking to the categories.  For instance, males are not ranked higher than females or vice versa – there is no order or rank, just different names assigned to each.  Other examples of nominal variables are: Religion, Marital status, and Race

7.  At this level, variables can be ranked-ordered. Example: Social class or status Upper class Middle class Lower class In ordinal variables, the distance between categories does not have any meaning.

8. at this level, the distance between the attributes, or categories, does have meaning.  Example: Temperature the distance between 30 and 40 degrees Fahrenheit is the same as the distance between 70 and 80 degrees Fahrenheit. But have no absolute, or fixed, zero point the gaps between the numbers of the scale are meaningful

9.  Represents fixed measuring and an absolute zero point ( zero means absolutely no amount of whatever the variable indicates Example: 10 is two points higher than 8 and is also two times greater than 5  Ratio numbers can be added and subtracted; they can be multiplied and divided.

10. ACTIVITY Directions: Fill in the table on the next page with the required information by identifying the level of measurement of the variable (nominal/ordinal/interval/ratio) and providing attributes/values/categories of the variable. VARIABLE LEVEL OF MEASUREMENT ATTRIBUTE/VALUE/ CATEGORY OCCUPATION RELIGION CITIZENSHIP CRIME RATE VOTING AGE

11. INDEXES and SCALES  A rating scale is used to capture a respondent’s reactions or responses to a given item in the scale

12.  A composite measure based upon multiple nominal-level indicators. This composite might be the sum of responses to the indicator items or some other calculation, such as the mean. Each indicator is given equal weight in measuring the construct. INDEX

13.  An “exercise” index, for example, might be the total score (0-5) of whether one participated in five different physical activities in the past week. In this example, we want to know only whether one participated in the physical activity at all during the past week. INDEX

14. A composite measure based upon multiple continuous-level indicators. This composite might be the sum of responses to the indicator items or some other calculation, such as the mean. Responses to each indicator vary in their strength and therefore in their contribution to the total score for the construct. SCALES

15. an index: a combination of items into a single score a scale: assigning scores to patterns of responses INDEXES vs SCALES

16. Item Selection Face Validity : The extent to which items seem to correspond to the definition of the construct (see also: content, logical). Dimensionality : Items intended to measure a construct should be exclusive to that construct. There are special exceptions to this criterion, such as in multi-trait, multi-method models. Variance : Items should have a strong correlation with the construct being measured. INDEX CONSTRUCTION

17. Handling Missing Data There are no perfect solutions to the problem. One might: Omit cases with missing data on any items. Insert the mean of all cases to items with missing data. Use specialized statistical procedures to estimate a value for the missing data. INDEX CONSTRUCTION

18. Index Validation Item Analysis : Examination of the empirical contribution of each item to measuring the construct (see also: internal validity). External Validation : Examination of the extent to which the construct is correlated with related constructs (see also: empirical validity). Bad Index or Bad Validators? : A lack of external validation might occur because the validating construct is not measured well. INDEX CONSTRUCTION

19. nominal scales consisting of binary items that assume one of two possible values , such as yes or no, true or false, and so on an also employ other values, such as male or female for gender, full-time or part-time for employment status, and so forth If an employment status item is modified to allow for more than two possible values (e.g., unemployed, full-time, part-time, and retired), it is no longer binary, but still remains a nominal scaled item. BINARY SCALES

20. BINARY SCALES

21. designed by Rensis Likert very popular rating scale for measuring ordinal data (esp. social science research) This technique assesses the extent of the subject’s agreement with items that have been judged (extent of agreement) to have content validity with the construct being measured. For example, the researcher might ask the respondent to 1) strongly disagree; 2) disagree; 3) neither agree nor disagree; 4) agree; or 5) strongly agree with the statement, “I am a person of worth” as a means of measuring self-esteem. LIKERT SCALES

22. LIKERT SCALES

23. LIKERT SCALES

24. a composite (multi-item) scale This technique assesses the extent of the subject’s agreement with items, where the response for each item is shown on a continuum. Example : Skipping class in Sociology is... Good for me. 1 2 3 4 5 Bad for me S EMANTIC DIFFERENTIAL SCALES

25. S EMANTIC DIFFERENTIAL SCALES

26. S EMANTIC DIFFERENTIAL SCALES

27. designed by Louis Guttman, another composite scale uses a series of items arranged in increasing order of intensity of the construct of interest, from least intense to most intense This technique assesses the extent of the subject’s agreement with items, where the items are meant to represent a continuum. GUTTMAN SCALES

28. For example, one might ask these questions: Do you drink alcohol? Do you smoke marijuana? Do you use cocaine? One might anticipate that all persons who answer “yes” to #3 would also answer “yes” to #1 and #2, and so forth. The technique provides continuous-level and ranked data. GUTTMAN SCALES

29. GUTTMAN SCALES