Notes

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Internal consistency analyses showed that both spelling tests were relatively unidimensional and displayed good internal consistency, although the recognition test contained too many easy items. Item-level analyses are included to provide the basis for further refinement of these instruments. The spelling tests were moderately correlated with the other measures of written language proficiency, but factor analyses revealed that they consistently defined a separate component, demonstrating that they tap a dimension of variability that is partially independent of variance in reading comprehension, speed, and vocabulary. These components appear to align with the precision and coherence dimensions of lexical quality.Eye-tracking is widely used throughout the scientific community, from vision science and psycholinguistics to marketing and human-computer interaction. Surprisingly, there is little consistency and transparency in preprocessing steps, making replicability and reproducibility difficult. To increase replicability, reproducibility, and transparency, a package in R (a free and widely used statistical programming environment) called gazeR was created to read and preprocess two types of data gaze position and pupil size. For gaze position data, gazeR has functions for reading in raw eye-tracking data, formatting it for analysis, converting from gaze coordinates to areas of interest, and binning and aggregating data. For data from pupillometry studies, the gazeR package has functions for reading in and merging multiple raw pupil data files, removing observations with too much missing data, eliminating artifacts, blink identification and interpolation, subtractive baseline correction, and binning and aggregating data. The package is open-source and freely available for download and installation https//github.com/dmirman/gazer. We provide step-by-step analyses of data from two tasks exemplifying the package's capabilities.Zemblys et al. (Behavior Research Methods, 51(2), 840-864, 2019) reported on a method for the classification of eye-movements ("gazeNet"). I have found three errors and two problems with that paper that are explained herein. Error 1 The gazeNet classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200 Hz. Of the six datasets that were used as the training set for the gazeNet algorithm, two were actually collected at 200 Hz. Problem 1 has to do with the fact that even among the 500 Hz data, the inter-timestamp intervals varied widely. Problem 2 is that there are many unusual discontinuities in the saccade trajectories from the Lund University dataset that make it a very poor choice for the construction of an automatic classification method. Error 2 The gazeNet algorithm was trained on the Lund dataset, and then compared to other methods, not trained on this dataset, in terms of performance on this dataset. see more This is an inherently unfair comparison, and yet nowhere in the gazeNet paper is this unfairness mentioned. Error 3 arises out of the novel event-related agreement analysis employed by the gazeNet authors. Although the authors intended to classify unmatched events as either false positives or false negatives, many are actually being classified as true negatives. True negatives are not errors, and any unmatched event misclassified as a true negative is actually driving kappa higher, whereas unmatched events should be driving kappa lower.Moving from the lab to an online environment opens up enormous potential to collect behavioural data from thousands of participants with the click of a button. However, getting the first online experiment running requires familiarisation with a number of new tools and terminologies. There exist a number of tutorials and hands-on guides that can facilitate this process, but these are often tailored to one specific online platform. The aim of this paper is to give a broad introduction to the world of online testing. This will provide a high-level understanding of the infrastructure before diving into specific details with more in-depth tutorials. Becoming familiar with these tools allows one to move from hypothesis to experimental data within hours.BACKGROUND Falls/fractures are major causes of morbidity and mortality among older adults and the resulting health consequences generate a substantial economic burden. Risk factors are numerous and include overactive bladder (OAB) and anticholinergic use. OBJECTIVES We aimed to estimate the impact of falls/fractures on all-cause healthcare resource utilization and costs, according to levels of cumulative anticholinergic burden, among individuals with OAB. METHODS Among a US cohort of adults with OAB (identified based on medical claims for OAB or OAB-specific medications), the frequency of resource utilization (outpatients visits, medication use, and hospitalizations) was examined according to level of anticholinergic burden. Anticholinergic burden was assessed cumulatively using a published measure, and categorized as no, low, medium, or high. Resource utilization prior to and after a fall/fracture was compared. Generalized linear models were used to examine overall and incremental changes in healthcare resource utilization and costs by fall/fracture status, and annual costs were predicted according to age, sex, fall/fracture status, and level of anticholinergic burden. RESULTS The mean age of the OAB cohort (n = 154,432) was 56 years, 68% were female, and baseline mean anticholinergic burden was 266.7 (i.e. a medium level of burden); a fall/fracture was experienced by 9.9% of the cohort. All estimates of resource utilization were higher among those with higher levels of anticholinergic burden, regardless of fall/fracture status, and higher for all levels of anticholinergic burden after a fall/fracture. Among those with a fall/fracture, the highest predicted annual costs were observed among those aged 66-75 years with high anticholinergic burden (US$22,408 for males, US$22,752 for females). CONCLUSIONS Falls/fractures were associated with higher costs, which increased with increasing anticholinergic burden.
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