Robust effect sizes and their confidence intervals for group difference between trajectories in hierarchical linear growth model

Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

Left, right and interval bivariate censored data: Evaluating screening mammography in the presence of lead -time bias, length bias and over-detection

Of the large clinical trials evaluating screening mammography efficacy, none included women ages 75 and older. Recommendations on an upper age limit at which to discontinue screening are based on indirect evidence and are not consistent. Screening mammography is evaluated using observational data from the SEER-Medicare linked database. Measuring the benefit of screening mammography is difficult due to the impact of lead-time bias, length bias and over-detection. The underlying conceptual model divides the disease into two stages: pre-clinical (T0) and symptomatic (T1) breast cancer. Treating the time in these phases as a pair of dependent bivariate observations, (t0,t1), estimates are derived to describe the distribution of this random vector. To quantify the effect of screening mammography, statistical inference is made about the mammography parameters that correspond to the marginal distribution of the symptomatic phase duration (T1). This shows the hazard ratio of death from breast cancer comparing women with screen-detected tumors to those detected at their symptom onset is 0.36 (0.30, 0.42), indicating a benefit among the screen-detected cases. ^

Operator and replicability bias in comparative taphonomic studies

The operator effect is a well-known methodological bias already quantified in some taphonomic studies. However, the replicability effect, i.e., the use of taphonomic attributes as a replicable scientific method, has not been taken into account to the present. Here, we quantified for the first time this replicability bias using different multivariate statistical techniques, testing if the operator effect is related to the replicability effect. We analyzed the results reported by 15 operators working on the same dataset. Each operator analyzed 30 biological remains (bivalve shells) from five different sites, considering the attributes fragmentation, edge rounding, corrasion, bioerosion and secondary color. The operator effect followed the same pattern reported in previous studies, characterized by a worse correspondence for those attributes having more than two levels of damage categories. However, the effect did not appear to have relation with the replicability effect, because nearly all operators found differences among sites. Despite the binary attribute bioerosion exhibited 83% of correspondence among operators it was the taphonomic attributes that showed the highest dispersion among operators (28%). Therefore, we conclude that binary attributes (despite showing a reduction of the operator effect) diminish replicability, resulting in different interpretations of concordant data. We found that a variance value of nearly 8% among operators, was enough to generate a different taphonomic interpretation, in a Q-mode cluster analysis. The results reported here showed that the statistical method employed influences the level of replicability and comparability of a study and that the availability of results may be a valid alternative to reduce bias.

Fluxes and meteorological observations on Spitsbergen

Arctic permafrost may be adversely affected by climate change in a number of ways, so that establishing a world-wide monitoring program seems imperative. This thesis evaluates possibilities for permafrost monitoring at the example of a permafrost site on Svalbard, Norway. An energy balance model for permafrost temperatures is developed that evaluates the different components of the surface energy budget in analogy to climate models. The surface energy budget, consisting of radiation components, sensible and latent heat fluxes as well as the ground heat flux, is measured over the course of one year, which has not been accomplished for arctic land areas so far. A considerable small-scale heterogeneity of the summer surface temperature is observed in long-term measurements with a thermal imaging system, which can be reproduced in the energy balance model. The model can also simulate the impact of different snow depths on the soil temperature, that has been documented in field measurements. Furthermore, time series of terrestrial surface temperature measurements are compared to satellite-borne measurements, for which a significant cold-bias is observed during winter. Finally, different possibilities for a world-wide monitoring scheme are assessed. Energy budget models can incorporate different satellite data sets as training data sets for parameter estimation, so that they may constitute an alternative to purely satellite-based schemes.

Biostratigraphy, magnetostratigraphy, granulometry, isotopes and clay mineral composition of ODP Site 188-1165

During Ocean Drilling Program Leg 188 to Prydz Bay, East Antarctica, several of the shipboard scientists formed the High-Resolution Integrated Stratigraphy Committee (HiRISC). The committee was established in order to furnish an integrated data set from the Pliocene portion of Site 1165 as a contribution to the ongoing debate about Pliocene climate and climate evolution in Antarctica. The proxies determined in our various laboratories were the following: magnetostratigraphy and magnetic properties, grain-size distributions (granulometry), near-ultraviolet, visible, and near-infrared spectrophotometry, calcium carbonate content, characteristics of foraminifer, diatom, and radiolarian content, clay mineral composition, and stable isotopes. In addition to the HiRISC samples, other data sets contained in this report are subsets of much larger data sets. We included these subsets in order to provide the reader with a convenient integrated data set of Pliocene-Pleistocene strata from the East Antarctic continental margin. The data are presented in the form of 14 graphs (in addition to the site map). Text and figure captions guide the reader to the original data sets. Some preliminary interpretations are given at the end of the manuscript.

Model parameter

Interannual environmental variability in Peru is dominated by the El Niño Southern Oscillation (ENSO). The most dramatic changes are associated with the warm El Niño (EN) phase (opposite the cold La Niña phase), which disrupts the normal coastal upwelling and affects the dynamics of many coastal marine and terrestrial resources. This study presents a trophic model for Sechura Bay, located at the northern extension of the Peruvian upwelling system, where ENSO-induced environmental variability is most extreme. Using an initial steady-state model for the year 1996, we explore the dynamics of the ecosystem through the year 2003 (including the strong EN of 1997/98 and the weaker EN of 2002/03). Based on support from literature, we force biomass of several non-trophically-mediated 'drivers' (e.g. Scallops, Benthic detritivores, Octopus, and Littoral fish) to observe whether the fit between historical and simulated changes (by the trophic model) is improved. The results indicate that the Sechura Bay Ecosystem is a relatively inefficient system from a community energetics point of view, likely due to the periodic perturbations of ENSO. A combination of high system productivity and low trophic level target species of invertebrates (i.e. scallops) and fish (i.e. anchoveta) results in high catches and an efficient fishery. The importance of environmental drivers is suggested, given the relatively small improvements in the fit of the simulation with the addition of trophic drivers on remaining functional groups' dynamics. An additional multivariate regression model is presented for the scallop Argopecten purpuratus, which demonstrates a significant correlation between both spawning stock size and riverine discharge-mediated mortality on catch levels. These results are discussed in the context of the appropriateness of trophodynamic modeling in relatively open systems, and how management strategies may be focused given the highly environmentally influenced marine resources of the region.

Sediment geochemistry, foraminiferal fauna parameter, census counts and Varimax PC-factor loadings and scores of foraminiferal assemblages of sediment core GeoB12615-4

Analogous to West- and North Africa, East Africa experienced more humid conditions between approximately 12 to 5 kyr BP, relative to today. While timing and extension of wet phases in the North and West are well constrained, this is not the case for the East African Humid Period. Here we present a record of benthic foraminiferal assemblages and sediment elemental compositions of a sediment core from the East African continental slope, in order to provide insight into the regional shallow Indian Ocean paleoceanography and East African climate history of the last 40 kyr. During glacial times, the dominance of a benthic foraminiferal assemblage characterized by Bulimina aculeata, suggests enhanced surface productivity and sustained flux of organic carbon to the sea floor. During Heinrich Stadial 1 (H1), the Nuttallides rugosus Assemblage indicates oligotrophic bottom water conditions and therefore implies a stronger flow of southern-sourced AAIW to the study site. During the East African Humid Period, the Saidovina karreriana Assemblage in combination with sedimentary C/N and Fe/Ca ratios suggest higher river runoff to the Indian Ocean, and hence more humid conditions in East Africa. Between 8.5 and 8.1 kyr, contemporaneous to the globally documented 8.2 kyr Event, a severe reduction in river deposits implies more arid conditions on the continent. Comparison of our marine data with terrestrial studies suggests that additional moisture from the Atlantic Ocean, delivered by an eastward migration of the Congo Air Boundary during that time period, could have contributed to East African rainfall. Since approximately 9 kyr, the gaining influence of the Millettiana millettii Assemblage indicates a redevelopment of the East African fringe reefs.