The volume assembles the voices of well-known psychologists speaking on methodological issues arising in psychological research. The thread that binds the papers together — the importance of the concept of probability — runs in four tangles:

Part I. Probability and the Idealizational Theory of Science

Marek Gaul’s paper considers the importance of the concept of probability in the paradigm of the idealizational conception of science. He criticizes the two approaches to probability proposed in the paradigm thus far: that of the theory’s founder, Leszek Nowak (1974, 1980), and that of Jerzy Brzezinski (1976, 1985), whose conception was particularly geared to the importance of the concept of probability in the behavioral sciences. Gaul then proposes a new way of thinking about the place of the concept of probability within the idealizational conception of science. His account enables to find theoretical space for statements on probability distributions.

Part II: Probability, Theoretical Concepts in Psychology, Measurement

The papers in the second part provide different perspectives on the importance of probability in both theoretical and experimental research in psychology (in particular in modeling). Douglas Wahlsten argues that we need to recognize the importance of probabilistic influences in shaping individual differences alongside with the two traditionally recognized factors: inheritance and environment. He considers the various levels in which probabilistic influences need to be taken more seriously in modeling individual differences than they have been so far. Bodo Krause in his paper presents a way of modeling cognitive learning, i.e. learning that does not require immediate feedback. The modeling of this type of learning is the more important that it enters crucially into productive or creative thinking. Dieter Heyer’s and Rainer Mausfeld’s paper is an illustration of one way in which the gap between theoretical realm and the realm of probabilistic measurement scales can be bridged. They demonstrate how psychophysical scales can be incorporated into substantive models of perceptual coding.

Part III: Methods of Data Analysis

In the third part, actual methods of data analysis are introduced and explored. Tadeusz B. IwiNski explores the applications Z. Pawlak’s (1986) rough set theory in psychology. Pawlak’s theory, just like Zadeh’s fuzzy set theory, attempts to formalize “vague” phenomena. The primary difference between these two approaches is that while the former understands vagueness in terms of being definable to some extent (and then one must somehow decide on the extent of the “extent”), the latter simply accepts the existence of “doubtful areas” whose properties are analyzed in terms of well-defined approximations. The theory has already found application in the areas of industrial control systems, expert systems, analysis of empirical data in medicine, and several rough logics have been construed. The author explores the various ways in which the method of rough analysis can find its application in psychology, in particular in the areas of decision making and human categorization. Wilma Koutstaal and Robert Rosenthal attempt to bring back into sight the neglected tool of contrast analysis. They review and compare several methods of computing contrasts. They demonstrate approaches to contrast analysis in between-subjects and repeated-measures designs. The authors emphasize the versatility, precision, and enhanced statistical power that contrast analysis allows to achieve.

Part IV: Artifacts in Psychological Research and Diagnostic Assessment

Finally, the fourth part of the book explores the eternal problem in all behavioral sciences, the problem of research artifacts. David B. Strohmetz and Ralph L. Rosnow propose a modification of one of the models of research artifacts presented originally by Rosnow and Aiken (1973). They suggest various strategies for controlling or eliminating systematic biases that appear in research with humans. Jerzy BrzeziNski’s paper deals with some methodological problems arising from the fact that diagnosis is essentially an interaction of two persons. He proposes a methodological frame in which the process can be conceptualized. He then asks the question whether, and if then to what extent, can diagnosis be ever externally valid, if we take into account the extent of the largely unconscious personal contributions of both participants of the diagnostic process.


Brzezinski, J. (1976). Struktura procesu badawczego w naukach behawioralnych (The Structure of the Research Process in Behavioral Sciences). Warsaw-Poznan: Polish Scientific Publishers PWN.

Brzezinski, J. (1985). The Protoidealizational model of the Investigative Process in Psychology. In: J. Brzezinski (Ed.), Consciousness: Methodological and Psychological Approaches (Poznan Studies in the Philosophy of the Sciences and the Humanities, 8). Amsterdam: Rodopi, pp. 36-57.

Nowak, L. (1971). U podstaw marksowskiej metodologii nauk. Wprowadzenie do idealizacyjnej koncepcji nauki (The Foundations of Marxian Methodology of the Sciences. An Introduction to the Idealizational Conception of Science). Warsaw-Poznan: Polish Scientific Publishers PWN.

Nowak, L. (1980). The Structure of Idealization. Dordrecht: Reidel.

Pawlak, Z. (1986). Rough Sets and Decision Tables. Lecture Notes, vol. 208. Berlin: Springer Verlag, 591-596.

Rosnow, R.L., & L.S. Aiken (1973). Mediation of Artifacts in Behavioral Research. Journal of Experimental Social Psychology, 9, 181-201.