CAUSAL-COMPARATIVE RESEARCH / Definition, types, characteristics, advantages , disadvantages, steps, procedure and Purpose of Causal-Comparative research design with examples
CAUSAL-COMPARATIVE RESEARCH / Definition, types, characteristics, advantages , disadvantages, steps, procedure and Purpose of Causal-Comparative research with examples / causal comparative research / causal comparative / causal comparative research design
CAUSAL-COMPARATIVE RESEARCH
Causal-comparative research is an attempt to identify a causative relationship between an independent variable and a dependent variable. The relationship between the independent variable and dependent variable is usually a suggested relationship (not proven) because you (the researcher) do not have complete control over the independent variable.
• Non-Experimental Designs that look into causal relationships.
• Researchers try to identify the causes of differences that already exists within individuals or groups
Causal-Comparative Research Facts
- Causal-Comparative Research is not manipulated by the researcher.
- Doesn't establish cause-effect relationships.
- Generally consists of extra than businesses and as a minimum one based variable.
- Independent variable is causal-comparative research is regularly called the grouping variable.
- The unbiased variable has happened or is already formed.
Main cause of causal-comparative research:
Exploration of Effects
Exploration of Causes Exploration of Consequences
Basic Characteristics of Causal-comparative studies
In brief it is the simple Characteristics of Causal-comparative studies may be concluded:
-Causal comparative studies tries to decide reasons, or reasons, for the prevailing condition
-Causal comparative research are also known as ex submit fact due to the fact the investigator has no manage over the exogenous variable. Whatever came about earlier than the researcher arrived.
-Causal-comparative studies is now and again dealt with as a kind of descriptive studies because it describes situations that already exist.
-Causal-comparative research try to pick out cause-impact relationships; correlational research do now no longer
-Causal-comparative research contain assessment, correlational research contain relationship.
-Causal-comparative research usually contain (or extra) corporations and one impartial variable, while correlational research usually contain or extra variables and one group
-Causal-comparative research usually contain (or extra) corporations and one impartial variable, while correlational research usually contain or extra variables and one group
-In causal-comparative the researcher tries to decide the cause, or reason, for preexisting variations in corporations of individual Involves assessment of or extra corporations on an unmarried endogenous variable.
-Retrospective causal-comparative research are a long way extra not unusual place in academic studies
-The simple method is now and again called retrospective causal- comparative studies (because it begins off evolved with results and investigates reasons)
-The simple method is now and again called retrospective causal- comparative studies (because it begins off evolved with results and investigates reasons)
-The simple causal-comparative method includes beginning with an impact and in search of viable reasons.
-The feature that differentiates those corporations is the exogenous variable.
-The version as potential causal-comparative studies (because it begins off evolved with reasons and investigates results)
We can by no means recognize with fact that the 2 corporations had been precisely identical earlier than the distinction came about.
Three critical elements of Causal Comparative approach are:
1- Gathering of information on elements always found in instances in which the given end result happens and discarding of these factors which aren't universally present.
2- Gathering the information on elements always found in instances in which the given impact does now no longer occur
3- Comparing the 2 units of information, or in impact, subtracting one from the alternative to get on the reasons chargeable for the prevalence or in any other case of the impact.
Examples of variables investigated in Causal-Comparative Research
-Ability variables (achievement)
-Family-associated variables (SES)
-Organismic variables (age, ethnicity, sex)
-Personality variables (self-concept)
-School associated variables (kind of school, length of school)
Types of Causal-Comparative Research Designs
There are styles of causal-comparative studies designs:
1. Retrospective causal-comparative studies
Retrospective causal-comparative studies calls for that a researcher starts off evolved investigating a selected query whilst the outcomes have already taken place and the researcher tries to decide whether one variable might also additionally have prompted any other variable.
2. Prospective causal-comparative studies
Prospective causal-comparative studies takes place whilst a researcher initiates a examine starts off evolved with the reasons and is decided to research the outcomes of a condition. By a way, retrospective causal-comparative studies designs are a lot greater not unusual place than potential causal-comparative designs.
Steps
. Develop the studies query
• Identify the unbiased and structured variable
• Select assessment companies
• Collect statistics from pre-present statistics
• Analyze and interpret the statistics
• Report findings
Basic method of causal- comparative studies
The researcher take a look at that 2 companies vary on a few variable (coaching style) after which try and locate the purpose for (or the consequences of) this difference.
1- Causal-comparative research, try and perceive motive-impact relationships.
2- Causal-comparative research normally Involve (or greater) companies and one unbiased variable
3- Causal-comparative research contain assessment.
4- The simple causal-comparative method includes beginning with an impact and in search of viable reasons (retrospective).
5- Retrospective causal – comparative research are a way greater not unusual place in instructional studies.
Limitations
• There ought to be a pre-present unbiased variable, and also you can not manage it
• There is a loss of randomization
• Inappropriate interpretations can occur: making it tough to perceive motive and impact relationships
• There are frequently different variables that have an effect on the structured variable in preference to the unbiased variable
• Reversal causation might also additionally exist
• Possibility of issue choice bias
• Other threats: location, instrumentation, and lack of subjects
• Caution in deciphering consequences