Announcing a Special Issue of Personnel Psychology on
John R. Hollenbeck
Michigan State University
John Stuart Mill established three criteria for inferring causality, (a)
covariation, (b) temporal precedence, and (c) elimination of alternative
explanations. Although philosophers of science still debate many aspects of what
is meant by the term "cause," there is widespread consensus among
working scientists regarding the appropriateness of these three rules. When
attempting to infer cause within this framework, Mill emphasized the need for a
scientist's active control over the independent variable. Active manipulation is
critical in science because it allows one to clearly establish temporal
precedence, and it is highly instrumental in the process of eliminating
alternative explanations for empirically documented covariation.
Although not necessarily familiar with Mill or the classic works in the
philosophy of science regarding causation, practicing managers and professionals
within contemporary organizations are also concerned with causal relationships.
Publications aimed at practitioners note the need for "learning
organizations" or "knowledge-creating companies," where knowledge
is operationalized in terms that would be very familiar to Mill. That is, the
competitive advantage that accrues from knowledge is manifested in the ability
to control certain outcomes (e.g., customer satisfaction, employee satisfaction
or shareholder satisfaction) via the manipulation of policies and programs in a
manner that is superior to one's rivals (Nonake, 1991; Gavin, 1993).
Applied psychologists help bridge the gap between psychological science and
organizationally based psychological practice, and much of applied psychological
research takes place within organizations. Even though these settings rarely
afford the luxury of manipulating variables and then randomly assigning
participants to conditions, there are a whole host of formal quasi-experimental
designs that do not require random assignment. In addition, many of these
designs make excellent use of "naturally occurring" manipulations for
inferring causal relationships, and hence point directly to potential applied
interventions. Given the boundary-spanning role of applied psychologists, and
the joint concern for establishing causal relationships among scientists and
practitioners, one might think that the use of quasi-experimental research
designs that involve active manipulation (or exploit naturally occurring
manipulations) would be widespread in this discipline. This, however, is not
generally the case.
Cook, Campbell, and Peracchio (1990) noted that "in reviewing the major
journals devoted to industrial and organizational psychology, we have been
struck by the relative paucity of field experiments." My experience over
the last 3 years as editor of Personnel Psychology has led me to the same
conclusion. Rather than using structural features of research design to
eliminate alternative explanations for results, applied psychologists rely more
heavily on statistical adjustments and modeling to perform the same function. In
some cases, this is as simple as partialling the effects or demographic
variables prior to examining the effects for purported causes, and in other
cases, this involves highly sophisticated approaches based upon structural
Although there is real value in these passive approaches to control, it is
easy to forget that partial correlations and weights derived from structural
equation modeling use covariance evidence to estimate relationships that are
presumed to be causalthey do not directly test causality. Even the most
recent versions of LISREL, while powerful, do not permit one to go back in time
and establish temporal precedence from cross-sectional data. Thus, even while
acknowledging the value of statistical control procedures, it seems that a case
can be made that we should supplement our science with more advanced use of
formally structured aspects of research design.
In order to help stimulate and promote the more frequent use of formal
quasi-experimental research designs, we are devoting a special edition of Personnel
Psychology to publishing research that uses these approaches to infer cause
in applied settings. The substantive area of the research can deal with any
topic that falls under the broad heading of applied psychology, but should focus
on manipulations or interventions that are evaluated via:
1. Formal two group designs such as the "untreated control group
design," the "untreated control group design with proxy pre
tests," the "untreated control group design with separate pre and post
tests," or the "untreated control group design, with reverse
2. Formal single group designs such as "the nonequivalent dependent
variable design" the "removed treatment design with pre and
posttests," the "repeated treatment design," and the
"regression discontinuity design."
3. Original or hybrid quasi-experimental designs that may differ in structure
from those described above, but are similar in their spirit of deriving rigorous
causal inferences based upon active manipulation of variables in field settings
that are not conducive to random assignment. This would exclude, however,
studies based upon the "one group pretest-posttest design" and
"posttest only design with nonequivalent groups."
All of these designs are described in detail by Cook and Campbell (1979), as
well as Cook, Campbell, and Peracchio (1990). When these formal designs are
supplemented with the type of rich contextual knowledge held by practitioners,
and sound substantive theory possessed by scientists, it is often possible to
establish covariation, temporal precedence, and eliminate alternative
explanations for results (such as selection or history artifacts) despite the
lack of random assignment. It is our belief that many scientists and
practitioners have access to (or can generate) data that is structured in this
fashion, and that framing this data in quasi-experimental terms will allow
meaningful contributions to the discipline's knowledge base regarding causal
relationships among the phenomena we study and manage.
The submission deadline for the papers that will be published as part of this
special edition is March 31, 2001.
Nonak, I. (1991). The knowledge creating company. Harvard Business Review,
Garvin, D. A. (1993). Building a learning organization. Harvard Business
Review, 81, 78-91.
Cook, T. D. and Campbell, D. T. (1979). Quasi-experimentation: Design and
analysis issues for field settings. Boston, MA: Houghton Mifflin.
Cook, T. D., Campbell, D. T., and Peracchio, L. (1990).
Quasi-experimentation. In M. D. Dunnette and L. M. Hough (Eds.) Handbook of
industrial and organizational psychology. Palo Alto, CA: Consulting
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