Variable

-

Definition of Variable:
Variable are properties or characteristics of people or things that vary in quality or magnitude from person to person or object to object (Miller & Nicholson, 1976). Variables could comprise of the following:

               

Demographic characteristics

Personality traits

Communication styles or competencies

Constructs
  

Operationalisation of variable:

Operationalisation:

Translating an abstract concept into a tangible, observable form in an experiment
Operationalisation’s can include

Variation in stimulus conditions (public school vs home schooling)

Variations in levels or degrees (mild vs. moderate vs. strong test approach)

Variations based on standardised scales or diagnostic instruments (low vs. high self-esteem scores)

Variation in “intact” or self- selected groups (smokers vs non-smokers

Varieties and Types of Variables:

1)    Discrete variables
     Nominal variables: distinct, mutually exclusive categories
o   Religion: Christians, Muslims, Jews, etc.
o   Occupations: Truck, driver, teacher, engineer
o   Marital status: single, married, divorced

2)    Concrete vs abstract variables
       §   Concrete: relatively fixed, unchanging
o         Biological sex
o         Ethnicity
§  Abstract, dynamic, transitory
o         Mood, emotion
o         Occupation 

3)    Dichotomous variables
        §  True/false, female/male, democrat/republican
§  Ordered variables: mutually exclusive categories but with an order, sequence or hierarchy
o    Fall, winter, summer, spring
o    K-6, Junior high, high school, college

4)    Continuous variables
     §  Include constant increments or gradations which can be arithmetically compared and contrasted
o    IQ Scores
o    Self-esteem scores
o    Age
o    Heart rate, blood pressure
o    Number of gestures

Tangible Vs Intangible Variable:

When picking up variables, researcher need to be very careful whether it is tangible variable or intangible variable. If it is intangible very difficult to penetrate into research frame especially in quantitative, but in qualitative, researcher can bring into different contextual because researcher is not going to measure it. In qualitative, we want to understand relationship between factors e.g. Independent vs Dependent Variables and not going to measure it.



Sources from: Professor Dr. Dileep Workshop on Role of Theory, Moderation & Mediation on 3 August 2019. 

Comments

Post a Comment

Popular posts from this blog

Analysing and Reporting Moderating Effect

-
First researcher should focus on the significance of the moderating effect (Z) To clarify, it is possible that a moderator variable (M) may or may not have an effect on the dependent variable (Y) Thus, the decision as to whether there is any moderating effect should be made based on a significance relationship between the moderating effect (Z) and the dependent variable (Y)     Second , researchers must calculate and report the effect size (f 2), and how much it contributes to R2 as a function of the moderator Only a few software packages (e.g. Smart PLS3.0) calculate f 2 by default For other there are online spreadsheets which can be used to calculate effect size (see: http://statwiki.kolobkreations.com ) Lastly, researchers must execute and report a simple slope plot for visual inspection of the direction and strength of the moderating effect SmartPLS users can check out a simple slope plot under ‘Final Results’ and ‘Simple Slope Analysis...
Read more

Proposal Construction: Chapter 1 to 3: Chapter 1 Part 3

-
Narrowing Down Research Topic: To narrow down your topic / focus area, you could ask these kind of questions: Whom for you doing the research? (Specific populations / Stakeholders) What are the factors you have taken for a research? is it relevant, contemporary or not? ( Relevant topic ) Where exactly you want to do the research? (Specific geographical area) This particular time when you do the research, is it relevant or not? (Specific time period) Why the issue occurs?  Example: Topic: Research Topic on Eating disorder Who –  Initially this topic is too broad, to make it narrower, we opt for population that we can focus on. Social demographic factor like: race, gender, age which are connected with eating disorder. So, the topic can be eating disorder in elderly female . You are connected gender, the age and disorder. We are fine tuning this problem into this factor.   What types of eating disorder -  2 types of eating disorder, ...
Read more

Approaches For Moderation Analysis

-
When performing statistical analysis using structural equation modelling, specifically in PLSSEM, there are several approaches for moderation analysis, including: Product- Indicator Two Stage Orthogonalizing  Prior to that, researcher must identify his or her theoretical frame falls under reflective construct or  just formative construct. Depending on researcher’s objective, he or she can choose any of the three approaches. 2-stage approaches has highest power, it is the most likely approaches to create significant attraction. It is recommended to make use of 2-stage approaches and make analysis. I f researcher has smallest population, he or she suppose to use orthogonalizing because the interaction effect size is the most correct and it maximises explained variance in his or her dependent variable. Product indicator approach has no particular advantage but still if it is formative construct can use product indicator approach Formative cons...
Read more