The application of HLM to the analysis of the dynamic interaction of environment, person and behavior - hierarchical linear modeling - A Special Issue: Focus on Hierarchical Linear Modeling

Over time, a person's behavior in an environment changes the environment and the someone These changes affect subsequent behaviors. Static conceptual and empirical prototypes of environments, persons and behavior cannot capture the processe involved. Dynamic prototypes of the complex interaction between environments, nation and behaviors, and analytic techniques for testing these originals are required. Conceptually, models have emerg that describe humans as self-regulating living combination of parts to form a wholes which both affect and are affected through their environments (Bandura, 1991; Carver & Scheier, 1981; Ford, 1987; Karoly, 1993; Latham & Locke 1991; Powers, 1973; Vancouver, in press) While these designs provide a way to think about the phenomenon, little empirical data has been generated that directly experiment many of the propositions in the patterns because of the complexity of the data analysis requirements. A lock opener source of complexity is set in the influence between multiple horizontals of analysis (Nesselroade & Ford, 1987) Fortunately, hierarchical linear modeling (HLM) is an analytic technique specifically unraveled to analyze multi-level models (Bryk & Raudenbush, 1992) In this close attention I apply HLM to analyze patterns derived from a self-regulating framework to examine more [i]or[/i] less of the interactions between the environment, one and behavior. The results of the application demonstrate the importance of the couple the self-regulating models and the use of appropriate analytic techniques for assessing like models.

The self-regulating framework's underlying mould is the negative feedback bight in which a task is monitored by the agency of comparing a goal for that task with perceptions of task progres If a discrepancy exists between the perception and the goal, an individual will attempt to bring the discrepancy by either altering the goal or applying resources to task-related behavior (Austin & Vancouver, in press; Klein, 1989; Lord & Hanges, 1987) Each discrepancy-reducing bight is one among many that defines a mixed hierarchical structure (Carver & Scheier, 1981; Miller, Galanter & Pribram, 1960; Powers, 1973) The simple bight has been used as an explanatory mechanism for single, goal-striving processe (Campion & Lord, 1982; Naylor & Ilgen, 1984) Consideration of multiple nooses has been advocated as an explanatory mechanism for more composite goal-striving processes (Keman & Lord, 1989; Klein, 1989; Lord & Hanges, 1987) on the contrary is rarely examined due to analysis difficulties (Nesselroade & Ford, 1987) Specifically, Nesselroade and Ford note that:

In living a whole s where it is the organization of the variables in patterns of mutual influence that sustains life and unfolding the power and generality of a multivariate approach is not alone attractive; it is essential. Moreover, because living combination of parts to form a wholes are open systems, it is impossible to understand their functioning separate from their words immediately preceding [i]or[/i] followings This requires a multivariate approach involving combinations of somebody and environment variables (p. 59)

As the complexity of interacting negative feedback bights increases, the consideration of bight processes and the dynamic interaction between the environment, someone and behavior becomes critical (Bandura, 1986; Kernan & Lord, 1989) Individuals 1) act upon and monitor many goals, 2) react to the observable effects of those actions and the opportunities and constraints provided by dint of the environment, and 3) assess strategies and resources straited to achieve the goals (eg Naylor, Pritchard & Ilgen, 1980) Together, this interaction shows a dynamic but potentially tractable, interplay of factors (Austin & Vancouver, 1996) In this investigation I examined that dynamic interaction by means of manipulating or measuring aspects of the environment, individual and behavior over time as they relate to goal striving.

Past Research

Past research upon goal striving has focused upon performance in single goal situations (see Locke & Latham, 1990 for a review). This research has clearly shown the merit of defining a specific and challenging goal to focus attention and other resources toward performance upon that goal. Yet, the part of feedback (Erez, 1977), goal acceptance and commitment (Hollenbeck & Klein, 1987) strategies (Wood & Locke 1990) and conflict among goals (Locke Smith, Erez Chah & Schaffer, 1994) have arisen as important variables when attempting to understand motivated behavior in mingled settings. In fact, most work situations require individuals to balance many goals and tasks (Kernan & Lord, 1989; Tsui & Ashford, 1994) Les is understood about the trade-offs individuals make in terminuss of resources and the interaction of the environment, somebody and behavior in these situations (Kernan & Lord, 1989 1990; Locke & Latham, 1990; forest-land Bandura & Bailey, 1990).

Studies using multiple goals are rare (Locke & Latham, 1990) and single goal studies ofttimes belie the processes involved. For example, Locke (1982) reported an asymptotic relationship between goal horizontal and performance. Specifically, he fix that as the goal horizontal reached impossible levels, the positive goal level-to-performance relationship wait oned to flatten at an ability ceiling. This indicated that make submissives continued to strive for the goal. However, in a multiple goal situation, the impossible goal might be pass overed in favor of an attainable goal that emergencys the resources used by the original goal. For instance, a public distinction is made between quantity and quality (eg Bavelas & to leeward 1978; Woodworth, 1899) aspects of a task. A public paradigm is to set a goal related to the number of satisfactory returnss thus combining the quantity and quality aspects (Locke & Latham, 1990) still when they are separated, many studies have ground that a specific, difficult quantity goal will repeatedly cause quality to suffer (Locke & Latham, 1990) or that a specific, difficult quality goal will cause quantity to undergo (Terborg & Miller, 1978).