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factors which might account for the non-significant relationships, among them low

statistical power or inaccurate ratings. Given the number of aggregate coworker and focal

pairs (N=107), weak relationships are not likely to reach statistical significance.

Specifically, the power to detect a correlation of moderate magnitude significantly

different from 0 in the population at p< .05 (e.g., r= .20) with a sample number of

respondents equal to 107 is equal to approximately .55 (Cohen, Cohen, West, & Aiken,

2002). In other words, type I error (the rejection of the null hypothesis when it is false) is

9 times more important than type II error (the failure to reject the null hypothesis/detect

significant effects). For a desired a power of .90 under the same parameter

specifications, 258 subjects would be required.


Moreover, the ratings provided by coworkers may also be biased by social

desirability or inaccuracy in spite of the researcher’s attempts to minimize biases.

Specifically, only cases who reported being familiar with the behaviors of the focal

employee were considered, and the raters were assured of the confidentiality of their

feedback, as well as its developmental rather than evaluative purposes, which could be

expected to result in higher truthfulness and reliability of the ratings (Pollack & Pollack,

1996). However, the focal employees were asked to select their raters, which is likely to

have resulted in their selection of friends who may provide inflated ratings (Murphy &

Cleveland, 1990).

The relationships between roles and supervisors’ ratings of behaviors were not

significant and, in fact, sometimes were opposite of their predicted direction. For

instance, innovative role had a negative albeit not significant relationship with supervisor

5 The importance of type I error relative to type II error may be judged by calculating the ratio of (1- power)/significance level (in this case, (1-.55)/.05.


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