1. AAA 3102 RESEARCH METHODOLOGY
Lecture 6
Level of Measurement
and Instrumentation

2. Levels of measurement
All variables of the research must be measured according to the four levels of measurement
Different statistical procedures need to be conducted according to the level of measurement
Besides statistical consideration, the level of measurement must be able to answer the specific objectives of the study or test the hypotheses
May combine the level of measurements in a questionnaire set, but each question must have its own level of measurement

3. Four levels of measurement: (Babbie, 2004)
Nominal measure – A variable whose attributes have only the characteristics of exhaustiveness and mutually exclusiveness
- A level of measurement describing a variable that has attributes that are merely different just like naming, labeling or categories
- Examples are gender, ethnic group and type of food that you like

4. Ordinal measure – A level of measurement describing a variable with attributes we can rank-order along some dimension
- There is a notion of low, medium high or small, medium large
- Examples are socio-economic status, level of education and intellectual sophistication

5. Interval measure – A level of measurement describing a variable whose attributes are rank-ordered and have equal distances between adjacent attributes
- There is equal quantity or distant between measures. However, zero does not mean absence off
- Examples is temperature and thermometer, ruler: the length between 3 to 5 inch is equal to the length between 8 to 10 inch

6. Ratio measure – A level of measurement describing a variable with attributes that have all the qualities of nominal, ordinal and interval measures and in addition are based on a ‘true zero’ point
- There is equal quantity or distant between measures and zero means absence off
- Examples is age, income and working experience

7. Criteria of measurement Quality (Babbie, 2004)
Precision and accuracy
- Precision concerns with the fineness of distinctions made between the attributes that compose a variable (e.g. youth at the age of 20 – 25 is more precise that youth in early twenties)
- Precise measurement is superior
- Exact precision is not always necessary
- Accuracy represents what is actually there in the real world
- Precise and accurate measurement will provide quality data are for quality research

8. Reliability – the quality of measurement method that suggests that the same data would have been collected each time in repeated observations of the same phenomenon
- A matter of whether a particular technique, applied repeatedly to the same object, yields the same research each time
- Example: question ‘Did you watch TV last night?’ would have higher reliability than the question ‘about how often you watch TV?’
- Reliability can be measured using statistical procedure

9. To cross-check the reliability of the measure or to improve the reliability of measure through: - Test-retest method
- Split-half method
- Using established measures
- Reliability of research workers

10. Validity – Describing a measure that accurately reflects the concept it is intended to measure
- Refers to the extend to which an empirical measure adequately reflects the real meaning of the concept under consideration
- Example we measure length using cm, measure time using hours, minutes and seconds, measure education by the qualification they achieved etc.
- Validity cannot be calculated using statistical procedure

11. Criteria of success in making measurements that are appropriate to meanings of concepts or the yardstick for assessing a measure’s validity include:
- Face validity
- Criterion-related validity
- Construct validity
- Content validity

12. We want our measures to be both reliable and valid
Try to measure a concepts in several ways
If the concept or variable has many dimensions, measure them all
After all, the concept or variable does not have any meaning other than what we had given
The justification of giving any concept a particular meaning is utility
Measure concepts in ways that help us understand the world around us

13. Researchers must choose from four levels of measurement that capture increasing amounts of information – nominal, ordinal, interval and ratio
The most appropriate level depends on the purpose of the measurement
A given variable can sometimes be measured at different level
When in doubt, researchers should use the highest level of measurement appropriate to that variable so they can capture the greatest amount of information

14. Instrumentation
To collect data from the respondents of research, there must be means or ways of doing it
Normally researchers use research instrument or questionnaire to collect the data
This topic deals with how to develop the research instrument or questionnaire
Questionnaire is a document containing questions and other types of items designed to solicit information appropriate for analysis

15. Questionnaires are used primarily in survey research but also in experiments, field research and other modes of observation
In quantitative research the questionnaire is more structured as compared to qualitative research
The questionnaire is valuable when we ask respondent questions they will respond with the appropriate data or information that will answer the research questions, research objectives and be able to conduct hypothesis testing

16. Typical categories of data:
- primary data: first hand, original, direct form respondents, directly related to problem, objectives, variables, and cost more
- secondary data: work has been done on the data, cost less, try to fit in what is available

17. - quantitative data: related to numbers and measurement is easy
- qualitative data: related to values, emotion and subjective, measurement is relatively difficult
- discrete data: a fixed quantity or attributes
- continuous data: amount can be further defined, fractions or decimals make sense

18. Research instrument or questionnaire is needed for:
- uniformity across respondents
- replicablity
- the exact information needed according to objectives and variables
- ease of data collection, process and analysis

19. In designing research instrument, consider:
- respondents of the study
- methods of data collection
- the amount of data
- resources in terms of money and personnel
- the time needed to complete data collection
- the flow of questions

20. In formulating questions in the research instrument, consider:
- the research problem, research questions, objectives, hypotheses and variables of the study
- the statistical procedures for data analysis
- the level of measurements
- the variables of the study
- instructions in answering the questions

21. - background information of the respondents
- the category of data required
- match the question(s) to research objectives, hypotheses and variables
- reliability and validity of data
- the language used to solicit response as well as to avoid confusion

22. Types of questions Closed-ended questions Open ended-questions
Choose one or more from list
Yes, no
Easy to analyze
Quantitative
Open ended-questions
Fill in the blanks
Others
Qualitative

23. Experience or behavioral questions
Related to what they had done in real life
Opinion or value questions
Related to their thoughts and views
Feeling questions
Related to their emotional reaction to certain thing

24. Knowledge questions
Related to what they know, right or wrong, facts
Reportorial questions
Related to what they see, read, hear or talk about
Devil’s advocate questions
Related to their views on controversial issues
Hypothetical questions
Related to their speculation about alternative occurrences

25. For closed-ended questions regarding
knowledge: Response – Right Wrong
attitude:
Response – Agree … Disagree
practice:
Response – Always … Never

26. The arrangement of questions in the research instrument can be in following ways:
Funnel format – broad open questions are used in the beginning followed by narrower and closed-ended questions that solicit more specific info.
Inverted funnel format – closed-ended questions are used in the beginning followed by broad, open questions

27. Tunnel format – straight or similar questions are organized throughout
The arrangement of questions will help the interviewers in establishing rapport with the respondents and thus facilitates the data collection process. At the same time, the respondents will build confident in answering the questions

28. Guidelines for asking questions
Choose appropriate questions forms
- questions and statements
- open-ended and closed-ended questions
Make items clear
Avoid double-barreled questions
Respondents must be competent to answer
Respondents must be willing to answer
Questions should be relevant
Short items are best
Avoid negative items, biased items and terms

29. What to do next?
Once the questionnaire is completed, get someone else to edit it
Have a cover letter that contains the title and purpose of study, request for cooperation, statement of confidentiality and contact number for further information. This letter must be signed and good to use letter head
THE QUESTIONNAIRE MUST BE PRE-TESTED BEFORE ACTUAL DATA COLLECTION