l9 variables and conceptual frameworks

Variables and Conceptual Frameworks

Ewnetu Firdawek

Outline

• Variables– Types of variables– Selecting Variables– Operational definition

• Conceptual Frameworks• Practical Session

Variables

• VARIABLE is a characteristic of a person, object, or phenomenon which can take on different values, which could be in the form of numbers or non-numerical characters.

• Example: weight, age, height, HIV status, Education, attitude• The properties of a data to be analyzed is described in certain

terms. • For the purpose of data description and statistical analysis data are

looked at as VARIABLES.• Data are classified basically as either NUMERICAL or

CATEGORICAL, and further classified.• NUMERICAL data are expressed in number.• CATEGORICAL data are expressed in classes or categories.

• Numerical data may be further classified as DISCRETE or CONTINUOUS variables.

• DISCRETE variables are those expressed in the form of whole numbers as 1, 2, 3, 4.– The value of a discrete variable does not take in between

whole numbers.– Example: the number of children a woman has, the number

of pregnancies, the number of sexual partners,

• CONTINUOUS variables are measured in a continuous scale.– These variables can take any value in between whole

numbers.– Example: Weight 7.23 kg, Height 1.56 m, Age,– A continuous variables can be grouped into ordered

categorical variables which are MUTUALLY EXCLUSIVE , i.e. no overlapping in groups, example in age groups as 0-4 years, 5-9 years, 10-14 years,….

• CATEGORICAL variables are ones where each individual is a member of one of the mutually exclusive classes.– Categorical data may be NOMINAL or ORDINAL.– NOMINAL data are not ordered to one above the other.– Example; sex(male or female), marital status (married,

divorced,..), religion, ethnicity, – ORDINAL data are ordered one above the other.– Example; grading of pain (mild, moderate, severe),

categorized educational status (illiterate, read and write, primary, secondary, tertiary),….

• In our problem analysis we have identified different factors that influence or affect our interest .

• These factors and our interest are also termed as variables.– Example: maternal death, waiting time, availability of

drugs, availability of trained health personnel, distance from health institution, women nutritional status, previous history of complications, superimposed diseases, …..

• However, the variable of our interest “Maternal Death” and the other variables relate differently, based on these relationships variables can be further classified.

• Variables can be classified further based on their interrelationship and the effect of one variable on the other.

• Commonly variables are classified as DEPENDENT and INDEPENDENT variables.

• But there are further classifications as MODERATOR, INTERVENING/INTERMEDIATE, DISTAL variables.

• DEPENDENT variables /Outcome, Endogenous, Response/

– This is the factor we are interested , or the response or outcome variable.

– The observed aspect of the behavior of an organism that has been stimulated.

– The factor to be observed and measured to determine the effect of other independent variables.

– It is the variable that can change as a result of the variation in the independent variable.

– It is called DEPENDENT because its values depends upon the values of the independent variable.

– Ex: CVSD are affected by weight, dietary habit, exercise, family Hx.

• INDEPENDENT Variables: /Explanatory, Exogenous/• It is a stimulus variable, or an input that operates either within

a person or within the environment to affect the status of the dependent variable.

• It is the factor to be measured or to be manipulated, in case of experimental studies, to determine its relationship with the observed phenomenon or dependent variable.

• As a characteristic, Independent variables are the cause for a change in the other variable, specifically on the dependent variable.

Example: Feeding habit affects nutritional status, HIV status is determined by sexual activity.

• INTERMEDIATE Variables: /Moderator/• These are variables which does not have direct relationship

with the outcome variable but affects the independent variable.• The change in the INTERMEDIATE variable determines the

value of the INDEPENDENT variable whereby the DEPENDENT variable.

• DISTAL / EXTERNAL Variables:• Are variables that are included to make the study

comprehensive and complete as much as possible in terms of the factors that affect the outcome variable.

• Such variables are usually expected to have an effect on the dependent or the intermediate variables.

• Example

What is confounding?

Maternal psychological morbidity during pregnancy

Infant diarrhoea in the first two months of life

(ever? frequency?)

Possible confounding variables

Variables that might be on the causal pathways

Logistic regression (if binary) or Poisson regression (if count )

Main interest

Why?

eg. educational level, infant gender, residence (urban/rural), sanitary condition of surrounding etc

eg. Sanitary practice, health seeking practice

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How do you measure?

READING ASSIGNMENT:2

Confounding Factors?Measures to Minimize Confounding effect?

Considerations to select Variables

• Objective of the study– Related to direct relation to the study

• Theoretical Consideration: – Related to theories – Related to literatures

• Design Considerations– Related to control and Bias/confounding effects– Related to the type of study design

• Practical Considerations– Related to resources– Can not cover all variables at a time– Specific to important variables

Operational Definitions

• Are working definitions.• Variables that are in use for particular study should be

defined in the context of that particular study.• However the definitions are not expected to be an

ordinary dictionary definitions though the definition should not deviate from its original meaning.

• Operationalization is the way used to make variables measurable, to be expressed in the form of numbers or concepts or called themes.

Ex:…

Operational Defin…..

Conceptual Frameworks

Conceptual Frameworks Vs. Conceptualization

CONCEPTUALIZATION: • Is the process of specifying and refining abstract concepts into

concrete terms.• Here the researcher needs to understand the general purpose of the

research, determine and identify relevant theories, literatures related to the topic and specify the meaning of the concepts and variables to be studied.

• Then formulate the general hypothesis, objective or research question.

• Done at the beginning of research project.

CONCEPTUAL FRAMEWORK:• Conceptual framework is by far a schematic representation

showing how different variables are interacted to each other and affects the dependent variable.

• The development of conceptual framework is basically dependent on the problem analysis tree and follows detail description of each variables under consideration within the literature review.

• Conceptual framework is a tool that helps the researcher to understand the situation under investigation.

• Having conceptual framework is helpful in the analysis and determination of the relationship of different variables to each other.

• Conceptual frameworks can take different structure, from the most simple and linear structure to complex structures.

Conceptual framework designed to show the effect of maternal employment on child nutritional status. (Birhanu Zenebe , AAU, Masters Thesis, 2000)

Conceptual frame work developed to show the factors that influence successful and sustained CBRHP (Daniel Argaw (MD), AAU Masters Thesis, 2002.

Assignment 3

Practical Session

Select study topicsSet objectivesIdentifying Study VariablesOperationalizing Study VariablesDeveloping Conceptual Frameworks

Thank you