‫מחקר פוליטי וסוציולוגי‬
‫איכותי‬
‫חקר‪-‬אירוע‬
‫‪N=1‬‬
‫מחקר‬
‫השוואתי‬
‫מחקר‬
‫השוואתי‬
‫‪N<50‬‬
‫‪N>1‬‬
‫כמותי‬
‫מחקר כמותי‬
‫‪N>50‬‬
‫מחקר פוליטי וסוציולוגי‬
‫מחקר ממוקד‪-‬מקרה‬
‫מחקר ממוקד‪-‬משתנים‬
‫‪N>7‬‬
‫מחקר כמותי‬
‫‪N>50‬‬
‫מחקר‬
‫השוואתי‬
‫‪N<50‬‬
‫‪N>1‬‬
‫‪N<7‬‬
‫‪N>1‬‬
‫חקר‪-‬אירוע‬
‫‪N=1‬‬
-‫מקרה למחקר ממוקד‬-‫בין מחקר ממוקד‬
‫משתנים‬
-‫• מחקר השוואתי ממוקד‬
‫מקרה מבקש להסביר‬
(diversity) ‫גיוון‬
• Typical example: why
Political Stability in
the Philippines while
instability all over
Latin America?
‫משתנים‬-‫• מחקר ממוקד‬
‫מבקש להסביר שונות‬
(VARIANCE)‫משותפת‬
• Typical example: to
what extent Economic
Development (X)
explains Political
stability (Y)?
X
Y
‫אסטרטגיות חקירה השוואתיות‬
‫בחירת המקרה‬
Most-Different
Research design
Most-Similar
Research Design
(Case-Oriented)
‫בחירת אספקטים‬
‫של המקרה‬
Method of
Agreement
Method of
Difference
‫בחירת אספקטים של המקרה‬
‫‪Method of‬‬
‫‪Agreement‬‬
‫קנדה יציבה‬
‫פוליטית‬
‫ארה”ב‬
‫יציבה פוליטית‬
‫‪Method of‬‬
‫‪Difference‬‬
‫איטליה‬
‫לא יציבה‬
‫ארה”ב‬
‫יציבה פוליטית‬
‫חיפוש אחרי גורמים מסבירים חיפוש אחרי גורמים מסבירים )‪ (X‬שונים‬
‫המשותפים גם לקנדה וגם ארה”ב המופעים או בארה”ב או באיטליה‬
The problem of analytical elimination:
Mill’s Method of Agreement
Case 1
Case 2
Case 3
I
j
k
l
x
e
f
g
h
x
a
b
c
d
x
Y
Y
Y
Key:
X = causal variable; Y= phenomenon to be explained
a, b,c,d, e, f, g, h, I, j, k, l = non-causal variables
possible
causal
variables
The problem of analytical elimination:
Mill’s Method of Difference
Negative
Case(s)
Positive
Case(s)
a
b
c
d
not x
a
b
c
d
X
Not Y
Y
Key:
X = causal variable; Y= phenomenon to be explained
a, b,c,d, e = non-causal variables
possible
causal
variables
The Problem of Control
Requires us to think about case-selection
Most Similar Design
Studies that make use of the MSSD are
based on the premise that systems as
identical as possible with regard to as
many constitutive features as possible
represent the optimal samples for
comparative research.
In the event that some important
differences are found…
"then the number of factors
attributable to these differences
will be sufficiently small to
warrant explanation in terms of
these differences alone”
(Przeworski and Teune,
1970, 117-26).
Most-Different Design
MDSD compares as contrasting
cases as possible in order to
show the robustness of a
relationship between dependent
and independent variables.
Such a design assumes that by
demonstrating that the
observed relationships hold in
a range of contrasting settings
the argument of the research is
better supported
The Problem of Control
Most Similar
Design
Control of
Background
Factors by
Specification
Explicit effort to maximize
control through
minimization of variance
Most-Different
Design
Control of
Background
Factors by
Specification
Control of
Background
Factors by
Randomization
Explicit effort to test
causation through
maximization
of variance
The Problem of Control
Requires us to think about case-selection
Most favorable Design
The most favorable
research design seeks initial
support for a theory by
testing it favorable conditions.
Least favorable Design
The least favorable
research design seeks to test a
theory in the crucial
circumstances where it is least
likely to hold up.
Maximizing Explanatory Power in
comparative research
Create sophisticated research design:
1. Use both MDSD and MDRD in case selection
2. Use least favorable conditions for testing causation
or argument
3. Use analytical elimination using both the method
of difference and method of agreement.
4. Allow for multiple conjunctural causation