variables & studytype
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Variables & Study Types
Aman Ullah
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ALERT: The materials included in this presentation was actually taught by
Dr. Tasleem Akhtarin the contact session of Master in Health Research at Khyber medical
university, Peshawar, Pakistan
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HYPOTHESES
Based on your experience with the study problem, it might be possible to develop explanations for the problem, which can then be tested.
A HYPOTHESIS is a prediction of a relationship between one or more factors and the problem under study that can be tested.
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VARIABLESA Variable is a characteristic of a person, object or phenomenon which can take on different values.
Example of a variable
•Age •weight•distance •Income etc
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Types of Variables:
•Numerical:
The values of all these variables are expressed in numbers
•Categorical:
These variables can only be expressed in categories.
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Numerical variables can either be continuous or discrete.
•Continuous. •Discrete.
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•ContinuousA continuous variable is one for which, within the limits the variable ranges, any value is possible.
With this type of data, one can develop more and more accurate measurements depending on the instrument used, e.g. height (CM) , temperature (degrees),
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•Discrete
These are variables in which numbers can only have full values, e.g. number of visits to a clinic, family members•
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Categorical variables can either be
1. ordinal or 2. nominal.
• Ordinal variables: These can be
Grouped and
Ordered or ranked in increasing or decreasing order
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• Nominal variables:
These can be grouped only Cannot be ordered or ranked
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Operationalising variables by choosing appropriate indicators
Operationalising variables means that you make them ‘measurable’ with one or more precise INDICATORS.
Examples: Level of Knowledge, Socio-economic status, IQ, awareness about a problem etc
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Defining variables and indicators of variables
To ensure that everyone understands exactly what has been measured and to ensure that there will be consistency in the measurement, it is necessary to clearly define the variables (and indicators of variables).
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Dependent and independent variables
Because in health research you often look for causal explanations, it is important to make a distinction between dependent and independent variables.
Contd.
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Dependant Variable
The variable that is used to describe or measure the problem under study is called the Dependent variable (The effect variable).
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Independent Variable
The variables that are used to describe or measure the factors that are assumed to cause or at least to influence the problem are called the Independent variables (cause variable).
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Confounding VariableA variable that is associated with the problem and with a possible cause of the problem is a potential Confounding Variable.
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A confounding variable may either strengthen or weaken the apparent relationship between the problem and a possible cause.
For example:
A relationship is shown between bottle-feeding and diarrhea in under-twos. However, mother’s education may be related to bottle-feeding as well as to diarrhea.
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STUDY TYPES
Several classifications of study types are possible, depending on what research strategies are used. Generally there are two broad categories:
1. Non- intervention Studies2. Intervention Studies
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1. Non-intervention studies in which the researcher just observes and analyses researchable objects or situations but does not intervene
2. Intervention studies in which the researcher manipulates objects or situations and measures the outcome of his manipulations
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NON-INTERVENTION STUDIES
•Descriptive studies
•Comparative (analytical) studies
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Descriptive studies
A Descriptive Study involves describing the characteristics of a particular situation, event or case.
•Small scale, descriptive case studies
•Large scale, cross-sectional surveys
•A stuy hat covers the total population is called a census.
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Comparative or analytical studies
An Analytical Study attempts to establish causes or risk factors for certain problems. This is done by comparing two or more groups, some of whom have the problem and some have not.
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Types of analytical studies
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Cross-sectional comparative studies
Two groups, one with the problem and another without it, are taken from the same population and compared for the presence of the independent variables/influencing factors, for the problem under study, at one point in time.
In any comparative study, one has to watch out for Confounding or Intervening variables.
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Case-control studies
In a Case-Control Study the investigator compares one group among whom the problem that he wishes to investigate is present, called the study group and
Compares it with another group without the problem, called the control group
Each case in the study group is matched with a control in the control group for background variables
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Diagram of a case-control study
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Cohort studies
In a Cohort Study, a group of individuals that is exposed to a risk factor (study group) is compared to a group of matched individuals not exposed to the risk factor (control group).
The researcher follows both groups over time and compares the occurrence of the problem that he expects to be related to the risk factor in the two groups
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Diagram of a cohort study
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INTERVENTION STUDIES
In intervention studies, the researcher manipulates a situation and measures the effects of this manipulation.
Types of intervention studies :
•Experimental studies and
•Quasi-experimental studies.
•Before and after studies
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Experimental studies
In an Experimental Study, individuals are randomly allocated to at least two groups.
One group is subject to an intervention, or experiment,
while the other group(s) is not.
The outcome of the intervention (effect of the intervention(independent variable) on the dependent variable/problem) is determined
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Diagram of an experimental study
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Quasi-experimental studies
In a Quasi-Experimental Study, one characteristic of a true experiment is missing, either randomisation or the use of a separate control group.
A quasi-experimental study, however, always includes the manipulation of an independent variable which is the intervention.
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Diagram of a quasi-experimental design
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Before-after study
Another type of design that is often chosen because it is quite easy to set up uses only one group in which an intervention is carried out.
The situation is analysed before and after the intervention to test if there is any difference in the observed problem.
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Diagram of a before-after study
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VALIDITY AND RELIABILITYWhat are validity and reliability in research findings?
Validity means that your scientific observations actually measure what they intend to measure (your conclusions are true).
Reliability means that someone else using the same method in the same circumstances should be able to obtain the same findings (your findings are repeatable).
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Questions/[email protected]