Researchers in many fields use multiple item scales to measure important variables such as attitudes and personality traits, but find that some respondents failed to complete certain items. Past missing data research focuses on missing entire instruments, and is of limited help because there are few variables to help impute missing scores and the variables are often not highly related to each other. Multiple item scales offer the unique opportunity to impute missing values from other correlated items designed to measure the same construct. A Monte Carlo analysis was conducted to compare several missing data techniques. The techniques included listwise deletion, regression imputation, hot-deck imputation, and two forms of mean substitution. Results suggest that regression imputation and substituting the mean response of a person to other items on a scale are very promising approaches. Furthermore, the imputation techniques often outperformed listwise deletion.

A survey instrument was developed and administered to 1,222 K-12 mathematics and science teachers to measure their beliefs about and use of inquiry in the classroom. Four variables (grade level taught, content area taught, level of support received, and self-efficacy for teaching inquiry) were significantly correlated to two dependent variables, percentage of time that students are engaged in inquiry during a typical lesson and the perceived ideal percentage of instructional time that should be devoted to inquiry. Specifically, elementary school teachers reported using inquiry-based practices more than either middle-school or high-school teachers; similarly, elementaryschool teachers believed such practices should be used more often. All groups, however, reported believing in an ideal percentage of time devoted to inquiry instruction that was significantly greater than their reported percentage of time actually spent on inquiry instruction. A disordinal effect was found between grade level taught and content area taught; at the elementary level, science teachers reported both an ideal and actual percentage of time on inquiry higher than those reported by the math teachers, while at the high school level math teachers reported both an ideal and actual percentage of time on inquiry higher than those reported by the science teachers. No correlations were found between typical and ideal percentage of time devoted to inquiry and subject matter content knowledge training, gender, years of teaching experience, or maximum degree earned.

The accuracy of eight missing data techniques (MDTs) under conditions of systematically missing data was tested using a Monte Carlo analysis. Data were generated from a population correlation matrix, then deleted using several patterns that might be found in a human resource management (HRM) selection validation study. The results indicated that listwise and pairwise deletion were the most accurate methods, followed closely by imputation methods such as regression and hot-deck. Mean substitution was substantially inferior to the other methods tested. Future research that examines different missing data patterns is recommended.

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What standard reports are included in TAP and SPP? What information is provided in item analysis output? How may teachers use the information in their instruction?