Measures Of Overlap Research Articles

Overlap Analysis in Progressive Hybrid Censoring: A Focus on Adaptive Type-II and Lomax Distribution

This article explores the adaptive type-II progressive hybrid censoring scheme, introduced by Ng et al. (2009), which is used to make inferences about three measures of overlap: Matusita's measure ($\rho $), Morisita's measure ($\lambda $), and Weitzman's measure ($\Delta $) for two Lomax distributions with different parameters. The article derives the bias and variance of these overlap measures' estimators. If sample sizes are limited, the precision or bias of these estimators is difficult to determine because there are no closed-form expressions for their variances and exact sampling distributions, so Monte Carlo simulations are used. Also, confidence intervals for these measures are constructed using both the bootstrap method and Taylor approximation. To demonstrate the practical significance of the proposed estimators, an illustrative application is provided by analyzing real data.

Will future wind power development in Scandinavia have an impact on wolves?

The global energy demand is growing, and the world is shifting towards using more renewable energy, like increased onshore wind power development. We used Global Positioning System (GPS) and Very High Frequency (VHF) location data from adult, territorial wolves Canis lupus in Scandinavia (Sweden and Norway; 1999–2021), to examine the potential for wind power development to affect wolf behavioural ecology. We examined the spatial overlap of areas proposed for wind power development with wolf territory activity centres prior to construction, to test to what extent overlap varies with season, time of day and social status (breeding versus non‐breeding wolves). Measures of overlap were the distance between wolf activity centre points and nearest proposed wind turbine, the probability of proposed wind turbines being within the activity centre, and the density of proposed wind turbines within the activity centre. The wolf activity centre points were closer to sites of proposed turbines in early summer than in late winter and the density of proposed turbines in the activity centre was higher in early summer than in late winter. These findings probably result from an altitudinal shift in wolf area use between summer and winter. We also found that the probability for proposed turbines to be within the activity centre was higher for non‐breeding than for breeding wolves during early summer, whereas it was higher for breeding compared to non‐breeding wolves during late winter. This difference might be an effect of that breeding wolves have a restricted area use during the early summer season (denning period), resulting in a lower probability of turbines being inside their activity centre as compared to late winter. There was no clear pattern for other seasonal and social status differences. The results should be viewed as a starting point for further research and supplemented with before‐after studies.

Cross-linguistic effects of form overlap in aural recognition of Spanish–English cognates

Abstract This study investigated the effect of cross-linguistic overlap in L1 and L2 auditory recognition of Spanish–English cognates. The study examined the correlation between objective and subjective measures of overlap and analyzed how these measures predict patterns in auditory recognition. 62 Spanish-speaking learners of English and 63 English-speaking learners of Spanish completed two auditory lexical decision tasks in Spanish and English and a rating task, where they rated the perceived phonological similarity of cognates. The results revealed moderate correlations between subjective and objective measures of overlap. While orthographic overlap had no effect, increased phonological overlap facilitated recognition in L1 and L2 Spanish and English and had larger effects in L2 recognition. Perceived similarity was the best predictor among the measures of overlap. The findings support models suggesting that cross-linguistic co-activation is facilitated by increased form similarity and studies reporting modality dependent effects of cross-linguistic form overlap in lexical recognition.

Acoustic vowel distances within and across dialects

Regional dialects of American English exhibit variation in the phonetic realization of vowel categories. This variation leads to different degrees of phonetic vowel similarity within and across dialects. This vowel similarity has been captured by measures of formant distance and overlap in the acoustic space, typically with static formant estimates from a single timepoint in the vowel. In contrast, dialect similarity has been assessed using measures of acoustic distance over time. In the current study, dynamic measures of acoustic distance, including dynamic time warping, root mean-square distance, and generalized additive mixed effect models, were used to assess within-dialect vowel category distances and to compare these distances across dialects. The results were generally consistent across the different distance metrics, confirming their respective ability to capture acoustic vowel distance. However, the magnitude of the distances varied across dialects and vowel variables. Whereas some dialect-specific variables showed the expected patterns of within- and across-dialect similarity based on previous descriptive work, other variables did not. These mixed findings have implications for our understanding of regional dialect variation in American English, its effect on acoustic vowel similarity, and the relationship between acoustic vowel similarity and perceptual ambiguity of vowel contrasts within and across dialects.

Interval estimation of the overlapping coefficients in an exponential family of distributions based on upper record values

This paper investigates interval estimation for measures of overlap, namely Matusita's measure, Weitzman's measure and based on Kullback–Leibler. Two types of sampling procedures, namely, Simple Random Sample and Upper Record Values from two exponential populations. Bootstrap method series approximation is used to construct confidence intervals for the overlap measures. To illustrate the performance of the likelihood confidence intervals obtained for this overlapping coefficient, under our proposal, we carry out some simulation studies that yield adequate coverage frequencies, this study conducts for comparing the performances of various competing estimators. A real data set is analysed to exemplify our proposal.

Abnormal Spatial and Temporal Overlap of Time-Varying Brain Functional Networks in Patients with Schizophrenia.

Schizophrenia (SZ) is a complex psychiatric disorder with unclear etiology and pathological features. Neuroscientists are increasingly proposing that schizophrenia is an abnormality in the dynamic organization of brain networks. Previous studies have found that the dynamic brain networks of people with SZ are abnormal in both space and time. However, little is known about the interactions and overlaps between hubs of the brain underlying spatiotemporal dynamics. In this study, we aimed to investigate different patterns of spatial and temporal overlap of hubs between SZ patients and healthy individuals. Specifically, we obtained resting-state functional magnetic resonance imaging data from the public dataset for 43 SZ patients and 49 healthy individuals. We derived a representation of time-varying functional connectivity using the Jackknife Correlation (JC) method. We employed the Betweenness Centrality (BC) method to identify the hubs of the brain's functional connectivity network. We then applied measures of temporal overlap, spatial overlap, and hierarchical clustering to investigate differences in the organization of brain hubs between SZ patients and healthy controls. Our findings suggest significant differences between SZ patients and healthy controls at the whole-brain and subnetwork levels. Furthermore, spatial overlap and hierarchical clustering analysis showed that quasi-periodic patterns were disrupted in SZ patients. Analyses of temporal overlap revealed abnormal pairwise engagement preferences in the hubs of SZ patients. These results provide new insights into the dynamic characteristics of the network organization of the SZ brain.

A comprehensive array of gray matter labels for the MIITRA atlas: Interoperability with complementary atlases

AbstractBackgroundA comprehensive array of gyral‐based,cytoarchitecture‐based,and functional connectivity‐based gray matter labels were constructed in the Multichannel Illinois Institute of Technology & Rush university Aging (MIITRA) atlas space in order to enhance the functionality of the atlas and its interoperability with complementary atlases.MethodT1w images from the 400 older adults included in the construction of the MIITRA atlas (50%male;64.9‐98.9 years of age) were processed with Freesurfer’s standard recon‐all pipeline. The Freesurfer outputs for all images were manually edited. Parcellations from Yeo,Desikan‐Killiany,HCP‐MMP,Brainnetome,Brodmann,Destrieux,Campbell,Flechsig,Mindboggle,Kleist,Smith,and EconomoCT atlases were projected onto the surface of each image and then converted to volumetric labels. The T1w images were also nonlinearly registered using ANTs‐SyN to the MNI152‐6thgen,MNI‐Colin,and the MNI‐2009b templates, and volumetric labels from Harvard‐Oxford,Julich,AAL3,Buckner,CoBrALab,CAREN,Striatum‐subdivision and Hippocampal‐subfields atlases were warped to the space of each image. The ANTs‐derived transformations applied on individual T1w images to build the MIITRA T1w template were used to map the corresponding gray matter labels from raw space to exact physical locations in the final MIITRA space. The performance of the MIITRA gray matter labels in segmentation of the gray matter of a separate group of 100 older adult individuals was evaluated in terms of label overlap, geometry, and dissimilarity when comparing the MIITRA labels warped to each individual’s space, to the respective reference labels from the source atlases.ResultExamples of the gray matter labels in MIITRA space are shown in Figure1. The measures of overlap between the warped and reference labels for each set of labels were generally high, with an average Dice coefficient of 0.78±0.3, average Jaccard coefficient of 0.59±0.27(Fig.2), sensitivity of 0.74±0.1, and specificity of 0.86±0.35(Fig.3). The label geometry showed a high correlation both in terms of the average volume of each label(correlation coefficient = 0.997,p‐value<10−10) and in terms of the average surface area of each label(correlation coefficient = 0.991,p‐value<10−10)(Fig.4). The values of dissimilarity were low, with an average volume error of 0.38±0.2(Fig.5).ConclusionThe gray matter labels in the MIITRA, in combination with the high‐resolution T1w template of the atlas, allowed segmentation of the gray matter of older adults that is in good agreement with the reference labels from the source atlases.

Evaluating simple measures of spatial-temporal overlap as a proxy for encounter risk between a protected species and commercial fishery

Spatial and temporal assessments of overlap are becoming increasingly popular as indicators of encounter risk. The overlap in distributions between protected species and commercial fishing effort is of interest for reducing bycatch. We explored overlap between the U.S. Atlantic sea scallop fishery and loggerhead turtles (Caretta caretta) using 2 metrics, and we assessed the ability of one of those metrics to track estimated fishery interactions over time. Moderate overlap occurred between June - September; mild overlap in the spring (May) and fall (October - November); and relatively little overlap from December to April. Qualitatively, there appeared to be some correspondence between the overlap values averaged across months for each calendar year and published annual loggerhead interaction estimates with fisheries, but the predictive performance of the overlap metric was low. When data on the relative distributions of commercial fishing effort and protected species are available, simple measures of spatial and temporal overlap can provide a quick and cost-effective way to identify when and where bycatch is likely to occur. In this case study, however, overlap was limited in helping to understand the relative susceptibility of protected species to commercial fishing (i.e., magnitude of interactions). We therefore caution against using overlap as a meaningful predictor of absolute risk unless there is direct evidence to suggest a relationship.

Sonority sequencing and its relationship to articulatory timing in Georgian

This work asks how the syllable as a unit is delimited in space and time. To do this we bring together two theoretical approaches to the syllable: a sonority-based approach which emphasizes spatial organization, and the coupled oscillator model (Nam, Goldstein & Saltzman 2009) which emphasizes temporal organization. Many languages present challenges to these theories, and here we focus on Georgian, which is problematic for both approaches, as Georgian permits onset clusters of up to seven consonants and of any sonority shape. Specifically, this study examines the relationship between gestural overlap and sonority shape in Georgian via electromagnetic articulography. Drawing on data from three speakers, we examine gestural overlap in two-consonant onsets that vary in sonority shape and order of place of articulation. Using two measures of gestural overlap, we find (i) long lag between consonant gestures, which we suggest is language-specific and (ii) that lag is largest in sonority rises and smallest in sonority falls. These results suggest that neither phonemic recoverability nor a hierarchical effect of increasingly open constrictions is the primary motivator behind inter-consonantal timing. Instead, the high degree of overlap in sonority falls ensures their tautosyllabic parse, which would otherwise be threatened by intrusive vocoids. Thus, we argue that recoverability of the syllable as a unit is the major motivating factor behind the timing patterns observed, and that syllables emerge not solely from either spatial or temporal properties, but from the interplay of the two.

Children’s Early Acquisition of Syntactic Category: A Corpus-Based Analysis of English Determiner-Noun Combinational Flexibility

While the generativist account posits that an abstract specification of syntactic categories is innate and children show adult-like performance from an early stage, the constructivist account postulates that children’s early acquisition of grammatical categories is item-based and reflects limited rules later. The present study tests these assumptions in a specific category, the English determiners. More specifically, we took the controlled measures of overlap (e.g., the use of definite article the and indefinite articles a/an before the same noun type) in 16 children and their mothers’ spontaneous speech as an indicator of determiner-noun combinational flexibility. A series of three studies were conducted, in which we strictly controlled the impact of differences between children and adults in lexical knowledge. In Study 1 and Study 2, we find that children’s use of determiners shows a significant difference from adults but this difference disappeared later. Furthermore, Study 3 investigates the influence of external environment with birth order and family’s social class as factors and emphasizes that the input factor is worthy of further investigation in future studies. These findings are consistent with one of the constructivist claims, namely that children’s early acquisition of determiners is not category-based and their flexibility in using determiners gradually approximates that of adults with development.

Children’s Early Acquisition of Syntactic Category: A Corpus-Based Analysis of English Determiner-Noun Combinational Flexibility

While the generativist account posits that an abstract specification of syntactic categories is innate and children show adult-like performance from an early stage, the constructivist account postulates that children’s early acquisition of grammatical categories is item-based and reflects limited rules later. The present study tests these assumptions in a specific category, the English determiners. More specifically, we took the controlled measures of overlap (e.g., the use of definite article the and indefinite articles a/an before the same noun type) in 16 children and their mothers’ spontaneous speech as an indicator of determiner-noun combinational flexibility. A series of three studies were conducted, in which we strictly controlled the impact of differences between children and adults in lexical knowledge. In Study 1 and Study 2, we find that children’s use of determiners shows a significant difference from adults but this difference disappeared later. Furthermore, Study 3 investigates the influence of external environment with birth order and family’s social class as factors and emphasizes that the input factor is worthy of further investigation in future studies. These findings are consistent with one of the constructivist claims, namely that children’s early acquisition of determiners is not category-based and their flexibility in using determiners gradually approximates that of adults with development.

Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study

Artificial intelligence (AI) and deep learning have shown great potential in streamlining clinical tasks. However, most studies remain confined to in silico validation in small internal cohorts, without external validation or data on real-world clinical utility. We developed a strategy for the clinical validation of deep learning models for segmenting primary non-small-cell lung cancer (NSCLC) tumours and involved lymph nodes in CT images, which is a time-intensive step in radiation treatment planning, with large variability among experts. In this observational study, CT images and segmentations were collected from eight internal and external sources from the USA, the Netherlands, Canada, and China, with patients from the Maastro and Harvard-RT1 datasets used for model discovery (segmented by a single expert). Validation consisted of interobserver and intraobserver benchmarking, primary validation, functional validation, and end-user testing on the following datasets: multi-delineation, Harvard-RT1, Harvard-RT2, RTOG-0617, NSCLC-radiogenomics, Lung-PET-CT-Dx, RIDER, and thorax phantom. Primary validation consisted of stepwise testing on increasingly external datasets using measures of overlap including volumetric dice (VD) and surface dice (SD). Functional validation explored dosimetric effect, model failure modes, test-retest stability, and accuracy. End-user testing with eight experts assessed automated segmentations in a simulated clinical setting. We included 2208 patients imaged between 2001 and 2015, with 787 patients used for model discovery and 1421 for model validation, including 28 patients for end-user testing. Models showed an improvement over the interobserver benchmark (multi-delineation dataset; VD 0·91 [IQR 0·83-0·92], p=0·0062; SD 0·86 [0·71-0·91], p=0·0005), and were within the intraobserver benchmark. For primary validation, AI performance on internal Harvard-RT1 data (segmented by the same expert who segmented the discovery data) was VD 0·83 (IQR 0·76-0·88) and SD 0·79 (0·68-0·88), within the interobserver benchmark. Performance on internal Harvard-RT2 data segmented by other experts was VD 0·70 (0·56-0·80) and SD 0·50 (0·34-0·71). Performance on RTOG-0617 clinical trial data was VD 0·71 (0·60-0·81) and SD 0·47 (0·35-0·59), with similar results on diagnostic radiology datasets NSCLC-radiogenomics and Lung-PET-CT-Dx. Despite these geometric overlap results, models yielded target volumes with equivalent radiation dose coverage to those of experts. We also found non-significant differences between de novo expert and AI-assisted segmentations. AI assistance led to a 65% reduction in segmentation time (5·4 min; p<0·0001) and a 32% reduction in interobserver variability (SD; p=0·013). We present a clinical validation strategy for AI models. We found that in silico geometric segmentation metrics might not correlate with clinical utility of the models. Experts' segmentation style and preference might affect model performance. US National Institutes of Health and EU European Research Council.

New measures for quantifying directional changes in presence-absence community data

Variation in community composition and species turnover are different types of beta diversity, expressing non-directional and directional changes, respectively. While directional changes (e.g. turnover) along geographic gradients can be studied in any direction depending on the hypothesis of interest to researchers, temporal changes can only be meaningfully studied from past to present. Although a wide variety of methods exist for partitioning variation and related community-level phenomena such as similarity, richness difference and nestedness, approaches evaluating species turnover along geographic or temporal gradients, based on an analogous conceptual framework, are rare. We therefore look into the possibilities for examining different aspects of directional changes along a gradient when presence-absence community data are available. Measures of community overlap, as well as species loss and gain from one sampling unit to another along a gradient are combined to define a variety of turnover and nestedness concepts and to derive functions for their quantification. Each concept represents an ecological phenomenon to be indicated (indicandum), whereas measures (indicators) quantify relevant properties of these concepts. The measures use the raw number of species as well as relativized forms in accordance with the well-known Jaccard and Sørensen indices. The main innovation is the development of new measures of directional community change. We demonstrate differences between traditional non-directional and the new directional measures and use several examples to show that actual communities display directional responses to a particular ecological gradient. The new measures therefore reveal an uncovered aspect of community ecology.

Development and evaluation of high‐resolution gray matter labels for the MIITRA atlas

AbstractBackgroundHigh resolution gray matter labels were constructed for the Multichannel Illinois Institute of Technology &amp; Rush university Aging (MIITRA) atlas based on manually edited gray matter labels of the older adults included in the atlas. The performance of the new labels in labeling the gray matter of a separate group of older adults was evaluated.MethodT1w images (400 images, 1mm isotropic) from the older adults included in the MIITRA atlas (50% male; 64.9‐98.9 age‐range; 54% white, 43% black) were processed with Freesurfer’s standard recon‐all pipeline, which segmented subcortical and cortical gray matter into 84 regions according to the Desikan Killiany atlas. The Freesurfer output for all images was manually edited. The ANTs‐derived transformations applied on individual T1w images to build the MIITRA T1w template were used to map the corresponding gray matter labels from raw space to exact physical locations in the final MIITRA space. The label in a 0.5mm isotropic voxel in MIITRA space was calculated using majority voting among all the labels that were mapped to that voxel. The performance of the MIITRA gray matter labels in segmentation of the gray matter of a separate group of 100 older adult individuals was evaluated in terms of label overlap, geometry, and dissimilarity when comparing the MIITRA labels warped to each individual’s space, to the respective manually edited reference labels.ResultExamples of the MIITRA gray matter labels and corresponding confidence maps are shown in Figure 1. The measures of overlap were generally high, with an average Dice coefficient of 0.82±0.10, Jaccard coefficient of 0.70±0.13 (Fig. 2), sensitivity of 0.77±0.13, and specificity of 0.89±0.09 (Fig. 3). There was a high correlation in label geometry both in terms of the average volume (correlation coefficient=0.997, p‐value&lt;10‐10) and in terms of the average surface area (correlation coefficient=0.988, p‐value&lt;10‐10) (Fig. 4). The values of dissimilarity were low, with an average volume error of 0.18±0.18 and an average Hausdorff distance of 8.69±8.78 (Fig. 5).ConclusionThe MIITRA gray matter labels, in combination with the high‐resolution T1w template of the atlas, allow segmentation of the gray matter of older adults that is in good agreement with the manually‐edited Freesurfer‐based segmentation.

Repeatability of Automated Image Segmentation with BraTumIA in Patients with Recurrent Glioblastoma.

Despite high interest in machine-learning algorithms for automated segmentation of MRIs of patients with brain tumors, there are few reports on the variability of segmentation results. The purpose of this study was to obtain benchmark measures of repeatability for a widely accessible software program, BraTumIA (Versions 1.2 and 2.0), which uses a machine-learning algorithm to segment tumor features on contrast-enhanced brain MR imaging. Automatic segmentation of enhancing tumor, tumor edema, nonenhancing tumor, and necrosis was performed on repeat MR imaging scans obtained approximately 2 days apart in 20 patients with recurrent glioblastoma. Measures of repeatability and spatial overlap, including repeatability and Dice coefficients, are reported. Larger volumes of enhancing tumor were obtained on later compared with earlier scans (mean, 26.3 versus 24.2 mL for BraTumIA 1.2; P < .05; and 24.9 versus 22.9 mL for BraTumIA 2.0, P < .01). In terms of percentage change, repeatability coefficients ranged from 31% to 46% for enhancing tumor and edema components and from 87% to 116% for nonenhancing tumor and necrosis. Dice coefficients were highest (>0.7) for enhancing tumor and edema components, intermediate for necrosis, and lowest for nonenhancing tumor and did not differ between software versions. Enhancing tumor and tumor edema were smaller, and necrotic tumor larger using BraTumIA 2.0 rather than 1.2. Repeatability and overlap metrics varied by segmentation type, with better performance for segmentations of enhancing tumor and tumor edema compared with other components. Incomplete washout of gadolinium contrast agents could account for increasing enhancing tumor volumes on later scans.

The Role of Acoustic Similarity and Non-Native Categorisation in Predicting Non-Native Discrimination: Brazilian Portuguese Vowels by English vs. Spanish Listeners

This study tests whether Australian English (AusE) and European Spanish (ES) listeners differ in their categorisation and discrimination of Brazilian Portuguese (BP) vowels. In particular, we investigate two theoretically relevant measures of vowel category overlap (acoustic vs. perceptual categorisation) as predictors of non-native discrimination difficulty. We also investigate whether the individual listener’s own native vowel productions predict non-native vowel perception better than group averages. The results showed comparable performance for AusE and ES participants in their perception of the BP vowels. In particular, discrimination patterns were largely dependent on contrast-specific learning scenarios, which were similar across AusE and ES. We also found that acoustic similarity between individuals’ own native productions and the BP stimuli were largely consistent with the participants’ patterns of non-native categorisation. Furthermore, the results indicated that both acoustic and perceptual overlap successfully predict discrimination performance. However, accuracy in discrimination was better explained by perceptual similarity for ES listeners and by acoustic similarity for AusE listeners. Interestingly, we also found that for ES listeners, the group averages explained discrimination accuracy better than predictions based on individual production data, but that the AusE group showed no difference.

On Inference of Overlapping Coefficients in Two Inverse Lomax Populations

Overlapping coefficient is a direct measure of similarity between two distributions which is recently becoming very useful. This paper investigates estimation for some well-known measures of overlap, namely Matusita’s measure ρ, Weitzman’s measure Δ and Λ based on Kullback–Leibler. Two estimation methods considered in this study are point estimation and Bayesian approach. Two inverse Lomax populations with different shape parameters are considered. The bias and mean square error properties of the estimators are studied through a simulation study and a real data example.

Coexistence of predatory caddisfly species may be facilitated by variations in the morphology of feeding apparatus and diet

Abstract The hypothesis of community‐wide character displacement (CWCD) predicts that coexisting species in the same guild should differ in morphological traits associated with resource acquisition, such that interspecific competition is unlikely. Hypothesis tests often focus on trophic structures involved in food acquisition, because variations in the morphology of foraging apparatus and diet composition may be directly related. Empirical evidence of such associations among sympatric guild members is, however, uncommon. The predatory larvae of caddisflies in the family Hydrobiosidae are ideal for studies of CWCD because the morphology of the prehensile foreleg, used to capture prey, varies markedly among genera. Further, hydrobiosids typically occur as species‐rich guilds, often with 10–20 species in a single community. Although the larvae are known to be predatory, detailed information on the diet of coexisting species is scarce. This study tested whether larval diet varied among multiple, sympatric species of hydrobiosid caddisflies that differed in foreleg morphology. Larval specimens were collected in summer and primarily from one river in central Victoria, Australia. Gut contents of late instar larvae were examined to describe diet composition, and diet was compared among taxa using measures of diet breadth and overlap. Seven sympatric species from six genera that differed in foreleg morphology were collected and late instar larvae were exclusively carnivorous. Diet composition and breadth varied markedly among some species, and diet was associated with morphology of the prehensile foreleg. Specialist predator species consumed predominantly chironomids and had high diet overlap. Generalists consumed primarily chironomids and mayflies, but overlap varied depending upon the preferred mayfly family and representation of other prey items, such as blackflies and insect eggs. All predator species consumed some caseless caddisflies and intraguild predation was strong in at least one species. The marked differences in diet and foreleg morphology among hydrobiosid species are consistent with the notion that CWCD influences guild membership and may facilitate species coexistence within guilds that are typically species‐rich. Although rarely considered for freshwater communities, CWCD may help explain species membership within other guilds. The magnitude of diet variations among genera within this family are more usually found across multiple families or orders, demonstrating that assumptions about the diet of even closely related taxa may be erroneous.

Addressing Validity and Generalizability Concerns in Field Experiments

In this paper, we systematically analyze the empirical importance of standard conditions for the validity and generalizability of field experiments: the internal and external overlap and unconfoundedness conditions. We experimentally varied the degree of overlap in disjoint sub-samples from a recruitment experiment with more than 3,000 public schools, mimicking small scale field experiments. This was achieved by using different techniques for treatment assignment. We applied standard methods, such as pure randomization, and the novel minMSE treatment assignment method. This new technique should achieve improved overlap by balancing covariate dependencies and variances instead of focusing on individual mean values. We assess the relevance of the overlap condition by linking the estimation precision in the disjoint sub-samples to measures of overlap and balance in general. Unconfoundedness is addressed by using a rich set of administrative data on institution and municipality characteristics to study potential self-selection. We find no evidence for the violation of unconfoundedness and establish that improved overlap, and balancedness, as achieved by the minMSE method, reduce the bias of the treatment effect estimation by more than 35% compared to pure randomization, illustrating the importance of, and suggesting a solution to, addressing overlap also in (field) experiments.

A comparison of four vowel overlap measures

Multiple measures of vowel overlap have been proposed that use F1, F2, and duration to calculate the degree of overlap between vowel categories. The present study assesses four of these measures: the spectral overlap assessment metric [SOAM; Wassink (2006). J. Acoust. Soc. Am. 119(4), 2334-2350], the a posteriori probability (APP)-based metric [Morrison (2008). J. Acoust. Soc. Am. 123(1), 37-40], the vowel overlap analysis with convex hulls method [VOACH; Haynes and Taylor, (2014). J. Acoust. Soc. Am. 136(2), 883-891], and the Pillai score as first used for vowel overlap by Hay, Warren, and Drager [(2006). J. Phonetics 34(4), 458-484]. Summaries of the measures are presented, and theoretical critiques of them are performed, concluding that the APP-based metric and Pillai score are theoretically preferable to SOAM and VOACH. The measures are empirically assessed using accuracy and precision criteria with Monte Carlo simulations. The Pillai score demonstrates the best overall performance in these tests. The potential applications of vowel overlap measures to research scenarios are discussed, including comparisons of vowel productions between different social groups, as well as acoustic investigations into vowel formant trajectories.