A Confirmatory Factor Analytic Study Examining the Dimensionality of Educational Achievement Tests

It is important to check the fundamental assumption of most popular Item Response Theory models, unidimensionality. However, it is hard for educational and psychological tests to be strictly unidimensional. The tests studied in this paper are from a standardized high-stake testing program. They feature potential multidimensionality by presenting various item types and item sets. Confirmatory factor analyses with one-factor and bifactor models, and based on both linear structural equation modeling approach and nonlinear IRT approach were conducted. The competing models were compared and the implications of the bifactor model for checking essential unidimensionality were discussed.

Relationships between soil nitrate desorbed from anion-exchange membranes, canopy reflectance and nitrate leaching losses from cool-season lawn turf.

Nutrient leaching studies are expensive and require expertise in water collection and analyses. Less expensive or easier methods that estimate leaching losses would be desirable. The objective of this study was to determine if anion-exchange membranes (AEMs) and reflectance meters could predict nitrate (NO3-N) leaching losses from a cool-season lawn turf. A two-year field study used an established 90% Kentucky bluegrass (Poa pratensis L.)-10% creeping red fescue (Festuca rubra L.) turf that received 0 to 98 kg N ha-1 month-1, from May through November. Soil monolith lysimeters collected leachate that was analyzed for NO3-N concentration. Soil NO3-N was estimated with AEMs. Spectral reflectance measurements of the turf were obtained with chlorophyll and chroma meters. No significant (p > 0.05) increase in percolate flow-weighted NO3-N concentration (FWC) or mass loss occurred when AEM desorbed soil NO3-N was below 0.84 µg cm-2 d-1. A linear increase in FWC and mass loss (p < 0.0001) occurred, however, when AEM soil NO3-N was above this value. The maximum contaminant level (MCL) for drinking water (10 mg L-1 NO3-N) was reached with an AEM soil NO3-N value of 1.6 µg cm-2 d-1. Maximum meter readings were obtained when AEM soil NO3 N reached or exceeded 2.3 µg cm-2 d-1. As chlorophyll index and hue angle (greenness) increased, there was an increased probability of exceeding the NO3-N MCL. These data suggest that AEMs and reflectance meters can serve as tools to predict NO3-N leaching losses from cool-season lawn turf, and to provide objective guides for N fertilization.

Efficiency Bounds for Estimating Linear Functionals of Nonparametric Regression Models with Endogenous Regressors

Consider a nonparametric regression model Y=mu*(X) + e, where the explanatory variables X are endogenous and e satisfies the conditional moment restriction E[e|W]=0 w.p.1 for instrumental variables W. It is well known that in these models the structural parameter mu* is 'ill-posed' in the sense that the function mapping the data to mu* is not continuous. In this paper, we derive the efficiency bounds for estimating linear functionals E[p(X)mu*(X)] and int_{supp(X)}p(x)mu*(x)dx, where p is a known weight function and supp(X) the support of X, without assuming mu* to be well-posed or even identified.