Methodological shifts in ratio-based modelling of corporate collapse

The year 1968 saw a major shift from univariate to multivariate methodological approaches to ratio-based modelling of corporate collapse. This was facilitated by the introduction of a new statistical tool called Multiple Discriminant Analysis (MDA). However, it did not take long before other statistical tools were developed. The primary objective for developing these tools was to enable deriving models that would at least do as good a job asMDA, but rely on fewer assumptions. With the introduction of new statistical tools, researchers became pre-occupied with testing them in signalling collapse. lLTUong the ratio-based approaches were Logit analysis, Neural Network analysis, Probit analysis, ID3, Recursive Partitioning Algorithm, Rough Sets analysis, Decomposition analysis, Going Concern Advisor, Koundinya and Purl judgmental approach, Tabu Search and Mixed Logit analysis. Regardless of which methodological approach was chosen, most were compared to MDA. This paper reviews these various approaches. Emphasis is placed on how they fared against MDA in signalling corporate collapse.

Determining the sensitivity of the Antarctic amphipod Orchomenella pinguides to metals using a joint model of survival response to exposure concentration and duration

Developing water quality guidelines for Antarctic marine environments requires understanding the sensitivity of local biota to contaminant exposure. Antarctic invertebrates have shown slower contaminant responses in previous experiments compared to temperate and tropical species in standard toxicity tests. Consequently, test methods which take into account environmental conditions and biological characteristics of cold climate species need to be developed. This study investigated the effects of five metals on the survival of a common Antarctic amphipod, Orchomenella pinguides. Multiple observations assessing mortality to metal exposure were made over the 30 days exposure period. Traditional toxicity tests with quantal data sets are analysed using methods such as maximum likelihood regression (probit analysis) and Spearman–Kärber which treat individual time period endpoints independently. A new statistical model was developed to integrate the time-series concentration–response data obtained in this study. Grouped survival data were modelled using a generalized additive mixed model (GAMM) which incorporates all the data obtained from multiple observation times to derive time integrated point estimates. The sensitivity of the amphipod, O. pinguides, to metals increased with increasing exposure time. Response times varied for different metals with amphipods responding faster to copper than to cadmium, lead or zinc. As indicated by 30 days lethal concentration (LC50) estimates, copper was the most toxic metal (31 µg/L), followed by cadmium (168 µg/L), lead (256 µg/L) and zinc (822 µg/L). Nickel exposure (up to 1.12 mg/L) did not affect amphipod survival. Using longer exposure durations and utilising the GAMM model provides an improved methodology for assessing sensitivities of slow responding Antarctic marine invertebrates to contaminants.

Bayesian hierarchical modeling of the temporal dynamics of subjective well-being: A 10 year longitudinal analysis

This study demonstrates, for the first time, how Bayesian hierarchical modeling can be applied to yield novel insights into the long-term temporal dynamics of subjective well-being (SWB). Several models were proposed and examined using Bayesian methods. The models were assessed using a sample of Australian adults (. n=. 1081) who provided annual SWB scores on between 5 and 10 occasions. The best fitting models involved a probit transformation, allowed error variance to vary across participants, and did not include a lag parameter. Including a random linear and quadratic effect resulted in only a small improvement over the intercept only model. Examination of individual-level fits suggested that most participants were stable with a small subset exhibiting patterns of systematic change.