The most frequently used experimental design type for research in industrial and organizational psychology and a number of allied fields is the nonexperiment. This design type differs from that of both the randomized experiment and the quasi-experiment in several important respects. Prior to describing the nonexperimental design type, we note that the article on实验设计in this section considers basic issues associated with (a) the validity of inferences stemming from empirical research and (b) the settings within which research takes place. Thus, the same set of issues is not addressed in this entry.
Attributes of Nonexperimental Designs
在几个重要方面,非实验设计与准实验设计和随机实验设计不同。总体而言,这些差异在内部有效性和其他几个标准方面,使用非实验设计的研究比使用替代设计的研究要弱得多。
Measurement of Assumed Causes
在非实验性研究中,假定原因的变量是测量的,而不是被操纵。例如,有兴趣测试组织承诺(假定原因)与工人生产率(假定效果)之间关系的研究人员必须衡量这些变量的水平。由于测量了承诺水平,该研究的内部有效性几乎没有。此外,请注意,多种数据分析策略(例如,路径分析,结构方程建模),这类研究的内部有效性根本无法改善,以允许对变量和变量之间的因果关系的推断(石材 -Romero,2002; Stone-Romero&Rosopa,2004)。
Nonrandom Assignment of Participants and Absence of Conditions
在非严重性的情况下,通常没有明确定义的研究条件。例如,有兴趣评估工作满意度(假定原因)和组织承诺(假定效果)之间关系的研究人员只会衡量这两个变量的水平。由于参与者没有随机分配到操纵工作满意度的条件下,因此研究人员将处于不舒服的位置,因为没有关于许多与工作满意度混淆的变量的信息。因此,研究的内部有效性将是一个主要问题。此外,即使研究涉及在研究人员无法控制的现有条件上的一个或多个因变量上的分数进行比较,研究人员也无法控制参与者在条件下的分配。例如,调查激励系统对多家制造公司公司生产力的假定影响的研究人员无法控制此类系统的属性。同样,这将大大降低研究的内部有效性。
Measurement of Assumed Dependent Variables
在非实验性研究中,测量假设的因变量。请注意,随机实验和准表现都相同。但是,在需要注意的三种实验设计类型之间存在非常重要的差异。更具体地说,在进行良好的随机实验的情况下,研究人员可以高度确信,对因变量的分数是研究操纵的函数。此外,在具有适当设计功能的准实例中,研究人员可以相当确信该研究的操纵负责观察到因变量的差异。但是,在非实验性研究中,研究人员处于不舒服的位置,必须假设他或她认为他或她视为依赖变量确实是影响。遗憾的是,在几乎所有非实验性研究中,这种假设都基于一个非常摇摇欲坠的基础。因此,例如,在研究工作满意度对退出工作意图的假定影响时,研究人员认为的效果实际上可能是原因。也就是说,出于认知一致性的利益,由于不基于工作满意的原因而决定辞职的个人认为自己的工作不满意。
Control Over Extraneous or Confounding Variables
Because of the fact that nonexperimental research does not benefit from the controls (e.g., random assignment to conditions) that are common to studies using randomized experimental designs, there is relatively little potential to control extraneous variables. As a result, the results of nonexperimental research tend to have little, if any, internal validity. For instance, assume that a researcher did a nonexperimental study of the assumed causal relation between negative affectivity and job-related strain and found these variables to be positively related. It would be inappropriate to conclude that these variables were causally related. At least one important reason for this is that the measures of these constructs have common items. Thus, any detected relation between them could well be spurious, as noted by Eugene F. Stone-Romero in 2005.
在hopes of bolstering causal inference, researchers who do nonexperimental studies often measure variables that are assumed to be confounds and then use such procedures as hierarchical multiple regression, path analysis, and structural equation modeling to control them. Regrettably, such procedures have little potential to control confounds. There are at least four reasons for this. First, researchers are seldom aware of all of the relevant confounds. Second, even if all of them were known, it is seldom possible to measure more than a few of them in any given study and use them as controls. Third, to the degree that the measures of confounds are unreliable, procedures such as multiple regression will fail to fully control for the effects of measured confounds. Fourth, and finally, because a large number of causal models may be consistent with a given set of covariances among a set of variables, statistical procedures are incapable of providing compelling evidence about the superiority of any given model over alternative models.
References:
- Cook, T. D., & Campbell, D. T. (1979). Quasi-experimentation: Design and analysis issues for field settings. Boston: Houghton Mifflin.
- Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin.
- Stone-Romero,E。F.(2002)。各种经验研究设计的相对有效性和实用性。在
- G. Rogelberg (Ed.), Handbook of research methods in industrial and organizational psychology (pp. 77-98). Malden, MA: Blackwell.
- Stone-Romero,E。F.(2005)。基于人格的污名和工作组织中的不公平歧视。在R. L. Dipboye和A. Colella(编辑)中,《工作中的歧视:心理和组织基础》(第255-280页)。新泽西州马瓦(Mahwah):劳伦斯·埃尔鲍姆(Lawrence Erlbaum)。
- Stone-Romero, E. F., & Rosopa, P. (2004). Inference problems with hierarchical multiple regression-based tests of mediating effects. Research in Personnel and Human Resources Management, 23, 249-290.