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

The self-regulating framework's underlying type is the negative feedback noose in which a task is monitored by means 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 composed of several elements hierarchical structure (Carver & Scheier, 1981; Miller, Galanter & Pribram, 1960; Powers, 1973) The simple noose 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 compound 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 exhibition the power and generality of a multivariate approach is not alone attractive; it is essential. Moreover, because living a whole s 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 individual and environment variables (p. 59)

As the complexity of interacting negative feedback nooses increases, the consideration of noose 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 ends of those actions and the opportunities and constraints provided by means 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 application of mind I examined that dynamic interaction by the agency 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 character 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 composed of several elements 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 limits of resources and the interaction of the environment, individual and behavior in these situations (Kernan & Lord, 1989 1990; Locke & Latham, 1990; copse Bandura & Bailey, 1990).

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