Gray Whales (Eschrichtius robustus) Off Sakhalin Island, Russia: Seasonal And Annual Patterns Of Occurrence

The annual return, seasonal occurrence, and site fidelity of Korean-Okhotsk or western gray whales on their feeding grounds off northeastern Sakhalin Island, Russia, were assessed by boat-based photo-identification studies in 1994-1998. A total of 262 pods were observed, ranging in size from 1 to 9 whales with an overall mean of 2.0'. Sixty-nine whales were individually identified, and a majority of all whales (71.0%) were observed in multiple years. Annual sighting frequencies ranged from 1 to 18 d, with a mean of 5.4 d. The percentage of whales re-identified from previous years showed a continuous annual increase, reaching 87.0% by the end of the study. Time between first and last sighting of identified individuals within a given year was 1-85 d, with an overall mean of 40.6 d. Annual calf proportions ranged from 4.3% (1997) to 13.2% (1998), and mother-calf separations generally occurred between July and September. The seasonal site fidelity and annual return of whales to this part of the Okhotsk Sea emphasize its importance as a primary feeding ground for this endangered population.

Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement

Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.