Absolute calibration and characterization of the multiband imaging photometer for Spitzer. I. The stellar calibrator sample and the 24 μm calibration

We present the stellar calibrator sample and the conversion from instrumental to physical units for the 24 μm channel of the Multiband Imaging Photometer for Spitzer (MIPS). The primary calibrators are A stars, and the calibration factor based on those stars is 4.54 × 10^-2 MJy sr^–1 (DN/s)^–1, with a nominal uncertainty of 2%. We discuss the data reduction procedures required to attain this accuracy; without these procedures, the calibration factor obtained using the automated pipeline at the Spitzer Science Center is 1.6% ± 0.6% lower. We extend this work to predict 24 μm flux densities for a sample of 238 stars that covers a larger range of flux densities and spectral types. We present a total of 348 measurements of 141 stars at 24 μm. This sample covers a factor of ~460 in 24 μm flux density, from 8.6 mJy up to 4.0 Jy. We show that the calibration is linear over that range with respect to target flux and background level. The calibration is based on observations made using 3 s exposures; a preliminary analysis shows that the calibration factor may be 1% and 2% lower for 10 and 30 s exposures, respectively. We also demonstrate that the calibration is very stable: over the course of the mission, repeated measurements of our routine calibrator, HD 159330, show a rms scatter of only 0.4%. Finally, we show that the point-spread function (PSF) is well measured and allows us to calibrate extended sources accurately; Infrared Astronomy Satellite (IRAS) and MIPS measurements of a sample of nearby galaxies are identical within the uncertainties.

A Comparison of Anchor-Item Designs for the Concurrent Calibration of Large Banks of Likert-Type Items

Current interest in measuring quality of life is generating interest in the construction of computerized adaptive tests (CATs) with Likert-type items. Calibration of an item bank for use in CAT requires collecting responses to a large number of candidate items. However, the number is usually too large to administer to each subject in the calibration sample. The concurrent anchor-item design solves this problem by splitting the items into separate subtests, with some common items across subtests; then administering each subtest to a different sample; and finally running estimation algorithms once on the aggregated data array, from which a substantial number of responses are then missing. Although the use of anchor-item designs is widespread, the consequences of several configuration decisions on the accuracy of parameter estimates have never been studied in the polytomous case. The present study addresses this question by simulation, comparing the outcomes of several alternatives on the configuration of the anchor-item design. The factors defining variants of the anchor-item design are (a) subtest size, (b) balance of common and unique items per subtest, (c) characteristics of the common items, and (d) criteria for the distribution of unique items across subtests. The results of this study indicate that maximizing accuracy in item parameter recovery requires subtests of the largest possible number of items and the smallest possible number of common items; the characteristics of the common items and the criterion for distribution of unique items do not affect accuracy.