Ragin’s comparative method

Characteristics comparative method

• Combinations of conditions are attributed causal value• Cases are studied as unique combinations of conditions

and are thus left intact• Explanations are absolute in that they cover all instances

of a phenomenon (no exceptions)• Examines all the cases of a population (does not

generalize from sample to population)• Makes use of categorical variables with two values:

present or absent; high or low; + or –• Aimed at making causal statements of limited

generalizability (bounded in time and space)

Characteristics statistical method

• Analytical (effect of each individual variable is determined independently of other variables)

• Cases are no more than the bearers of variables• Generalises from sample to population• Explanations are not absolute but probabilistic (i.e.

outliers and exceptions are accepted as long as there are not too many)

• Frequency is important (an explanation is stronger the more instances it covers)

• Intensity of phenomenon is taken into account (ordinal and continuous variables)

• Aimed at reaching conclusions with universal validity

When is Ragin’s comparative method a suitable approach?

• If explanatory unit of research is at a group level (school, municipality, region, country);

• If there are few units (e.g. less than 30);• If the response variable is categorical with binary

values (or can easily be turned into it);• If most of the explanatory variables presumed

important are binary or can be turned into binary ones;

• When you are interested in multiple causation;• To construct an empirical typology (pp 149-160

of Ragin’s book)

Ragin’s comparative method: how does it work?

A step by step approach:• Select cases and variables relevant to research interest and

hypotheses• Turn selected variables into binary variables and define values;• Assign present and absent values to each case on these variables

by using upper and lower case letters• Compile these values in a data matrix• Transform the data matrix into a truth table (p. 88 of Ragin’s book) A

truth table lists all the logically different combinations of values of the independent variables found in the sample

• Collect all the logically different combinations that produce the outcome

• Use Boolean algebra to arrive at a ‘primitive’ causal equation reflecting these combinations (F = ABc + aBc + Abc; p. 91)

Advantages Ragin’s method

• Applicable in situations of limited cases;• Statements can be made about combinations of

causes;• The integrity of cases as (unique) combinations

of properties is respected;• No problems with generalization from sample to

population;• Gives powerful explanations that cover all cases;• Convenient tool for constructing typologies.

Disadvantages Ragin’s method

• Does not distinguish between lower and higher level variables

• Difficult to transform higher level variables into binary ones. Problems:– distance between original values– variables with a normal distribution

• Frequency not taken into account in assessing strength of explanations

• Strict explanations covering all instances may contain so many combinations that interpretation becomes difficult (i.e. transparency and parsimony suffer)

• Only focuses on combinations linked with the presence of the outcome (i.e. only applies Mill’s method of agreement, not the method of difference)