Chapter 6 (SYA4300)

5 criteria for causal explanations

1. association 2. time order 3. non-spuriousness 4. causal mechanism 5. causal context - when a research design leaves one or more of the criteria unmet, we may have some important doubts about causal assertions the researcher may have made

four circumstances that increase confidence in drawing conclusions about time order on the basis of cross sectional data

1. the independent variable is fixed at some point PRIOR to the variation in the dependent variable 2. we believe that respondents can give us reliable reports of what happened to them or what they thought at some earlier point in time 3. our measures are based on records that contain information on cases in earlier periods 4. we know that the value of the dependent variable was similar for all cases prior to the treatment

causal explanation

One concept somehow leads to another A --> B (the independent variable (IV) is the presumed cause, and the dependent variable (DV) is the potential effect)

statistical control (criteria for causal explanations)

a method in which one variable is helf constant so that the relationship between two (or more) other variables can be assessed without the influence of variation in the control variable

randomization (criteria for causal explanations)

a technique used to reduce the risk of spuriousness - the greater the number of cases assigned randomly to the groups, the more likely that the groups will be equivalent in all respects

cross sectional research design

all data collected at one point in time (determining the time order of effects can be an insurmountable task)

association (criteria for causal explanations)

an empirical (or observed) association between the IV and the DV is the first criterion for identifying a nomothetic (probabilistic) causal effect - we can determine whether an association exists between the independent and dependent variables in a true experiment because there are two or more groups that differ in terms of their value on the IV - in non-experimental research, the test for an association between the independent and dependent variables is like that used in experimental research: seeing whether values of cases that differ on the IV tend to differ in terms of the DV

nonspuriousness (criteria for causal explanations)

another essential criterion for establishing the existence of a causal effect of an IV on a DV; in some respects, it is the most important criterion - we say that a relationship between two variables is not spurious when it is not due to variation in a third variable

time order (criteria for causal explanations)

association is a necessary criterion for establishing a causal effect, but it is not sufficient - we must also ensure that the variation in the DV occurred after the variation in the IV (this is the criterion of time order) - our research design determines our ability to determine temporal order (direction of influence) - in a true experiment the time order is determined by the researcher - cross-sectional designs do not establish the time order of effects, their conclusions about causation must be more tentative

repeated cross-sectional design (trend study)

data are collected at two or more points in time but from different samples of the same population

event-based design (cohort study)

data are collected at two or more points in time from individuals in a cohort (different samples within a cohort) (can be a type of repeated cross sectional or a type of panel design)

fixed-sample panel design (panel study)

data are collected at two or more points in time from the same individuals (the panel)

longitudinal research design

data collected at two or more points in time (identification of the time order of effects can be observed; data can be ordered in time)

what to do when level of analysis differs from what was actually studied?

do not reject conclusions but instead consider the likelihood that an ecological fallacy or a reductionist fallacy has been made

ecological fallacy

draws conclusions about individual level processes from group level data

three basic social research designs

experiments, surveys, and qualitative methods (all provide distinct perspectives, even when studying the same social processes)

nomothetic causal explanation

identification of a few causal factors that influence a class of conditions or phenomena - involves the belief that variation in an IV will be followed by variation in the DV, when all other things are equal (ceteris paribus) - researchers who claim a causal effect have concluded that the value of cases on the DV differs from what their value would have been in the absence of variation in the IV

causal context (criteria for causal explanations)

identification of the context in which a causal relationship occurs can help us to understand that relationship

the goal of most social science reserch

identifying causes

simple, direct causation

independent variable --> dependent variable

indirect causation

independent variable 1 --> dependent variable 1 (also independent variable 2); independent variable 2 --> dependent variable 2

multiple causation

independent variables (iv1, iv2, iv3) --> dependent variable

reductionist (individualist) fallacy

individuals are used to make inferences about group level processes

random sampling of larger populations....

is better suited for descriptive research intended to produce generalizable findings

what happens when units of analysis and units of observation aren't consistent

it misleads about the existence of an association between two variables

two approaches to causality

nomothetic (identification of a few causal factors that influence a class of conditions or phenomena) and idiographic (exhaustive identification of the specific or particular causes of a limited set of conditions or phenomena)

experimental designs test best for...

nomothetic causal hypotheses (also most appropriate for studying treatment effects)

our understandings of causal relationships are always...

partial - researchers always wonder whether they have omitted some relevant variables from their controls, whether their experimental results would differ if the experiment were conducted in another setting, or whether they have overlooked a critical historical event

laboratory experiments...

provide more control over conditions at expense of the generalizability of findings

Opposite of ecological fallacy

reductionist fallacy

three major types of longitudinal designs

repeated cross-sectional design (trend study), fixed-sample panel design (panel study), event-based design (cohort study)

conclusions about group-level processes

should be based on data collected about groups

conclusions about processes at the individual level

should be based on individual-level data

causal mechanism (criteria for causal explanations)

some process that creates the connection between variation in an IV and the variation in the DV it is hypothesized to cause

idiographic causal explanation

the concrete, individual sequence of events, thoughts, or actions that resulted in a particular outcome for a particular individual or that led to a particular event - may be termed an individualist or a historicist explanation

key elements of research design

the design's units of analysis and its use of cross sectional or longitudinal data

units of analysis

the level of social life on which the research question is focused (individuals, groups, towns, nations, families, schools, organizations, etc.) (in sociology units of analysis are most commonly individuals)

idiographic causal effect

when a series of concrete events, thoughts, or actions result in a particular event or individual outcome

nomothetic causal effect

when variation in an IV, leads to or results, on average, in variation in the DV - ex. individuals arrested for domestic assault tend to commit fewer subsequent assaults than do similar individuals who are accused in the same circumstances but not arrested