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Understanding Causality in Social Sciences: Mill's Methods and Experimental Designs, Lecture notes of Social Statistics and Data Analysis

The concept of causality in social sciences, focusing on mill's methods for determining causality and experimental designs. Mill's methods include the method of residue, agreement, concomitant variation, and difference. Experimental designs involve isolating a causal variable through exposure to a suspected cause and measuring the effect on the dependent variable. The document also covers research hypotheses, threats to internal validity, and the logic of research.

Typology: Lecture notes

2011/2012

Uploaded on 01/26/2012

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Social Explanation and Causality
A complete scientific explanation of a
social phenomenon would identify all
of the key causes.
Causation exists when one or more
variables is responsible for the
occurrence of another variable.
Causality implies a linking force
between variables. When Xcauses
Y; the occurrence of Xproduces
changes in Y.
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Social Explanation and Causality

A complete scientific explanation of a

social phenomenon would identify all

of the key causes.

Causation exists when one or more

variables is responsible for the

occurrence of another variable.

Causality implies a linking force

between variables. When X causes

Y ; the occurrence of X produces

changes in Y.

Mill’s “Methods” or “Canons” for

determining causality:

(1) Method of Residue ….an inductive method for determining causality. The researcher systematically investigates and tries to eliminate all possible causes.

 One or more of the possible causes that you cannot eliminate or rule out (the residual causes ), could be the ACTUAL CAUSE(s).

(3) Method of Concomitant Variation ….if a variable occurs in time & space with the phenomenon, the variable correlated with the phenomenon may be the cause. Why? If change in variable X is accompanied by change in variable Y , then X could be a cause of Y. (e.g., the higher the social support levels a person has, the better their mental & physical health will be). This is the basis for many causal inferences in sociology. NOTE: correlation implies but does not always prove causality!

(4) Method of Difference ….if some variable is present when the phenomenon of interest occurs, and is absent when the phenomenon does not occur. That variable may be the cause of the phenomenon.

 The logical basis for many causal inferences in psychology & sociology (e.g. experimental or quasi-experimental research, program evaluations, etc.).

 Does watching Jon Stewart’s “The Daily Show” make viewers cynical about politics?

Experimental Designs…an Introduction:

 Control variables: variables the researcher controls so the independent / dependent variable relationship can be isolated.

 Confounding variables: variables the researcher fails to control. Confounding variables can suppress or inflate evidence of a causal relationship between independent / dependent variables.

 Random variables: variables that may influence independent / dependent variable relationship; they are controlled for by randomly assigning subjects to groups.

More on Research Hypotheses...

 Where do hypotheses come from? Social theories, Research literature, Personal experiences, Commonsense, Intuition, Professional judgements.

 Clearly stated.

 Stated in value-free terms.

 Specific.

 Testable with existing research

methods (and existing or obtainable

data).

Research Problems or Questions &

Research Hypotheses

Problem/ Question : What causes political violence?

Research Hypotheses :

 1. The risk of political violence increases as the intensity of relative deprivation rises.

 2. The risk of political violence increases as the strength of religious ideas increase.

 3. The risk of political violence decreases as the perceived responsiveness of government increases.

Threats to Internal Validity

History: extraneous, noteworthy, public events that coincide with your research can provide a rival explanation for your findings.

Minimize the possible impact of

history with good planning &

speedy execution of research.

Threats to Internal Validity

 Testing: the measurement (or testing) a

researcher uses can alter the phenomenon we are measuring. Specific testing threats include: test experience , sensitizing , and evoking “socially appropriate” or “politically correct” responses.

 Measurement always has the potential to be “reactive”!

Threats to Internal Validity

 Instrumentation: when we use two

different measuring instruments

(ironically in order to minimize testing

bias), differences we measure could

arise from the different instruments

we used.

Threats to Internal Validity

Statistical Regression ….changes in any phenomenon tend to be toward the population mean/average. Extremes of any phenomenon tend to become less extreme over time.

 This is one reason why great athletes tend to have children who are less athletic…and why terrible athletes can have children who more athletic. Make sure the groups you are comparing are comparable and are not self-selected groups!!!

The Logic of Research: Experimental

Designs

Early designs assessed changes in a

D.V. due to an I.V.

Pre-experimental designs were

agricultural so researchers ignored

threats to internal validity.