A Time-Varying Dynamic Partial Credit Model to Analyze Polytomous and Multivariate Time Series Data.

The accessibility to electronic devices and the novel statistical methodologies available have allowed researchers to comprehend psychological processes at the individual level. However, there are still great challenges to overcome as, in many cases, collected data are more complex than the available models are able to handle. For example, most methods assume that the variables in the time series are measured on an interval scale, which is not the case when Likert-scale items were used. Ignoring the scale of the variables can be problematic and bias the results. Additionally, most methods also assume that the time series are stationary, which is rarely the case. To tackle these disadvantages, we propose a model that combines the partial credit model (PCM) of the item response theory framework and the time-varying autoregressive model (TV-AR), which is a popular model used to study psychological dynamics. The proposed model is referred to as the time-varying dynamic partial credit model (TV-DPCM), which allows to appropriately analyze multivariate polytomous data and nonstationary time series. We test the performance and accuracy of the TV-DPCM in a simulation study. Lastly, by means of an example, we show how to fit the model to empirical data and interpret the results.

Temporal changes in bird functional diversity across the United States.

Global changes are modifying the structure of species assemblages, but the generality of resulting diversity patterns and of their drivers is poorly understood. Any such changes can be detected and explained by comparing temporal trends in taxonomic and functional diversity over broad spatial extents. In this study, we addressed three complementary questions: How did bird taxonomic and functional diversity change over the past 40 years in the conterminous United States? Are these trends non-linear? Can temporal variations in functional diversity be explained by broad-scale changes in climate and vegetation productivity? We quantified changes in taxonomic and functional diversity for 807 bird assemblages over the past four decades (1970-2011) considering a suite of 16 ecological traits for 435 species. We found increases in local bird species richness and taxonomic equitability that plateaued in the early 2000's while total abundance declined over the whole period. Functional richness, the total range of traits in an assemblage, increased due to the rising prevalence of species with atypical life-history strategies and under-represented habitat or trophic preferences. However, these species did not trigger major changes in the functional composition of bird assemblages. Inter-annual variations in climate and primary productivity explained the richness of bird life-history traits in local assemblages, suggesting that these traits are influenced by broad-scale environmental factors, while others respond more to more local drivers. Our results highlight that a comparative analysis of the multiple facets of functional diversity can raise novel insights on processes underlying temporal trends in biodiversity.