Designing A/B Tests with Large Samples

2020 ◽  
pp. 91-105
Keyword(s):  
Large Samples

Electron Beam-Induced Mass Loss in Freeze-Dried Tissue and Protein Samples

1985 ◽  
Vol 43 ◽  
pp. 470-471
Author(s):  
M.E. Cantino ◽  
M.K. Goddard ◽  
L.E. Wilkinson ◽  
D.E. Johnson
Keyword(s):  
Electron Beam ◽  
Salivary Gland ◽  
Mass Loss ◽  
Counting Rate ◽  
Dose Dependence ◽  
X Ray ◽  
Large Samples ◽  
Freeze Dried ◽  
Muscle Homogenate ◽  
Large Muscle

Quantification in biological x-ray microanalysis depends on accurate evaluation of mass loss. Although several studies have addressed the problem of electron beam induced mass loss from organic samples (eg., 1,2). uncertainty persists as to the dose dependence, the extent of loss, the elemental constituents affected, and the variation in loss for different materials and tissues. in the work described here, we used x-ray counting rate changes to measure mass loss in albumin (used as a quantification standard), salivary gland, and muscle.In order to measure mass loss at low doses (10-4 coul/cm2 ) large samples were needed. While freeze-dried salivary gland sections of the required dimensions were available, muscle sections of this size were difficult to obtain. To simulate large muscle sections, frog or rat muscle homogenate was injected between formvar films which were then stretched over slot grids and freeze-dried. Albumin samples were prepared by a similar procedure. using a solution of bovine serum albumin in water. Samples were irradiated in the STEM mode of a JEOL 100C.

The "Core" of the Dark Triad: A test of competing hypotheses

2019 ◽  
Author(s):  
Colin Vize ◽  
Donald Lynam ◽  
Katherine Collison ◽  
Josh Miller
Keyword(s):  
Dark Triad ◽  
The Core ◽  
Large Samples ◽  
Parsimonious Explanation ◽  
Shared Variance ◽  
Competing Hypotheses ◽  
Callous Affect

As research on the Dark Triad (DT; the interrelated constructs of Machiavellianism, narcissism, and psychopathy) has accumulated, a subset of this research has focused on explicating what traits may account for the overlap among the DT members. Various candidate traits have been investigated, with evidence supporting several of them including Antagonism (vs. Agreeableness), Honesty-Humility, and Callousness and Interpersonal Manipulation (the latter two as a set). The present study sought to test the leading candidates against one another in their ability to account for the shared variance among the DT members. Using a pre-registered analytical plan, we found that Agreeableness (as measured by the IPIP-NEO-120), Honesty-Humility from the HEXACO, and the SRP-III subscales of Callous Affect and Interpersonal Manipulation accounted for all or nearly all of the shared variance among the DT members. BFI-based measures of Agreeableness (BFI and BFI-2) accounted for notably less variance in most cases. The results were consistent across two large samples (Ns of 627 and 628), and across various DT measurement approaches. We argue that the most parsimonious explanation for findings on the core of the DT is that such traits all fall under the umbrella of Antagonism.

Estimation in Large Samples

1988 ◽  
Author(s):  
Michael Woodroofe
Keyword(s):  
Large Samples

Microbial Sampling: Is It Better to Sample Many Times or Use Large Samples?

1993 ◽  
Vol 27 (3-4) ◽  
pp. 19-25 ◽  
Author(s):  
Charles N. Haas
Keyword(s):  
Small Volume ◽  
Negative Binomial ◽  
Dispersion Parameter ◽  
Microbial Quality ◽  
Large Samples ◽  
Repeated Sampling ◽  
Repeated Samples ◽  
Microbial Sampling

Repeated sampling of a water (raw, Ssished, recreational) is often used to assess microbial quality. Microbial distributions have often been found to be negative binomial distributed in such repeated samples. Under these conditions, it is shown that it is better to use a large number of small volume samples than vice versa, providing that the negative binomial dispersion parameter remains unaffected by volume. Further research is needed to determine if the latter assumption, which influences the conclusion proposed, is valid for various classes of microorganisms in various types of waters.

Computerized method for validating laboratory reference ranges for triiodothyronine and thyroxin immunoassays

1991 ◽  
Vol 37 (3) ◽  
pp. 438-442 ◽  
Author(s):  
Brian Luttrell ◽  
Sall Watters
Keyword(s):  
Reference Range ◽  
Normal Values ◽  
Reference Group ◽  
Normal Population ◽  
Normal Subjects ◽  
Reference Ranges ◽  
Large Samples ◽  
Laboratory Reference ◽  
Euthyroid Status ◽  
Computer Based

Abstract We used a computer-based method to help validate the reference ranges of assays for triiodothyronine (T3) and thyroxin (T4). A retrospective search of a database of laboratory results for the previous six months identified all patients with apparent euthyroid status, as defined by methods independent of the immunoassay under review. A computer-generated reference group (CGR Group) of 2001 records had a gaussian distribution of T4 values and a reference range (mean +/- 2 SD) of 56-161 nmol/L, compared with the supplier's suggested range for euthyroid subjects (58-148 nmol/L) and an in-house range of 60-144 nmol/L for a group of 97 normal subjects. A similar CGR Group of 1902 records gave a reference range for T3 of 0.7-2.1 nmol/L (manufacturer's range 0.8-2.8; normal subjects 0.8-2.2). An attempt to devise a reference range for thyrotropin failed when we found that its concentration in the population of patients with normal values for thyroid hormones was distributed differently from that in the normal population. The method is intended to be used in addition to conventionally derived ranges based on results for healthy subjects. It allows the laboratory to conveniently verify the reference ranges for T3 and T4 assays at regular intervals by using very large samples with appropriate age, sex, and weight distribution, drawn from the population of patients' samples submitted for analysis.

Adolescent Popularity as a Nonlinear, Two-Dimensional Construct: Convergent Results From Three Large Samples

2021 ◽  
pp. 027243162110160
Author(s):  
Peter E. L. Marks ◽  
Ben Babcock ◽  
Yvonne H. M. van den Berg ◽  
Rob Gommans ◽  
Antonius H. N. Cillessen
Keyword(s):  
Early Adolescents ◽  
Composite Score ◽  
Two Dimensional ◽  
Behavioral Correlates ◽  
Large Samples ◽  
Three Samples ◽  
Peer Nominations

The goal of this study was to advance the conceptualization and measurement of adolescent popularity by exploring the commonly used composite score (popularity minus unpopularity). We used standardized peer nominations from 4,414 early adolescents (ages ≈ 12-14 years) from three samples collected in two countries. Popularity and unpopularity were strongly related, but not linearly; scatterplots of the two variables resembled an L-shaped right angle. Subsequent analyses indicated that either including popularity as a curvilinear term or including both popularity and unpopularity as separate terms explained significantly more variance in social and behavioral correlates than linear, bivariate analyses using popularity, unpopularity, or composite popularity. These results suggest that researchers studying adolescent popularity should either separate popularity and unpopularity or treat composite popularity as curvilinear.

Conventional microscopy makes perikymata count and spacing data feasible for large samples

2021 ◽  
Author(s):  
Heather J. H. Edgar ◽  
Emily Moes ◽  
Cathy Willermet ◽  
Corey S. Ragsdale
Keyword(s):  
Large Samples ◽  
Conventional Microscopy

scholarly journals Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Daniel J. Panyard ◽  
Kyeong Mo Kim ◽  
Burcu F. Darst ◽  
Yuetiva K. Deming ◽  
Xiaoyuan Zhong ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Drug Targets ◽  
Large Scale ◽  
Prediction Models ◽  
Genome Wide Association ◽  
Large Samples ◽  
Genome Wide ◽  
Metabolomic Data ◽  
Related Phenotype ◽  
Omic Data

AbstractThe study of metabolomics and disease has enabled the discovery of new risk factors, diagnostic markers, and drug targets. For neurological and psychiatric phenotypes, the cerebrospinal fluid (CSF) is of particular importance. However, the CSF metabolome is difficult to study on a large scale due to the relative complexity of the procedure needed to collect the fluid. Here, we present a metabolome-wide association study (MWAS), which uses genetic and metabolomic data to impute metabolites into large samples with genome-wide association summary statistics. We conduct a metabolome-wide, genome-wide association analysis with 338 CSF metabolites, identifying 16 genotype-metabolite associations (metabolite quantitative trait loci, or mQTLs). We then build prediction models for all available CSF metabolites and test for associations with 27 neurological and psychiatric phenotypes, identifying 19 significant CSF metabolite-phenotype associations. Our results demonstrate the feasibility of MWAS to study omic data in scarce sample types.

scholarly journals Validity of Recreational Marathon Runners’ Self-Reported Anthropometric Data

2020 ◽  
Vol 127 (6) ◽  
pp. 1068-1078
Author(s):  
Pantelis T. Nikolaidis ◽  
Beat Knechtle
Keyword(s):  
Body Mass ◽  
Assessment Method ◽  
Fat Percentage ◽  
Anthropometric Data ◽  
Anthropometric Measures ◽  
Marathon Runners ◽  
Present Sample ◽  
Large Samples ◽  
Anthropometric Characteristics ◽  
Recreational Runners

While studies on large samples of recreational runners have often relied on participants’ self-reported height and body mass, the validity of these data have not been investigated for this population. Hence, this study sought to examine the validity of self-reported anthropometric measures among recreational marathon runners. Female ( n = 32) and male ( n = 135) recreational marathon runners were requested to estimate their body mass and height (and we calculated their self-reported body mass index [BMI]), after which we took actual measures of their body mass and height and calculated their actual BMI. Participants’ self-reported values underestimated their actual body mass by 0.65 kg ( p < .001, η2 = 0.222) and their actual BMI by 0.35 kg ⋅ m−2 ( p < .001, η2 = 0.245). There was a significant Assessment Method × Sex Interaction for both body mass ( p = .019, η2 = 0.033) and BMI ( p = .017, η2 = 0.034), as women underestimated body mass values more than men. Participants overestimated their height by 0.44 cm ( p < .001, η2 = 0.075), but the interaction of sex and assessment method for height was not statistically significant. Underestimates of body mass correlated with marathon racing speed ( r = .24, p = .006) and body fat percentage ( r = −.29, p = .001) in men, but not in women ( p > .05). The disagreement between self-reported and measured anthropometric data in the present sample was lower than has been previously reported for the general population, suggesting that marathon runners may more accurately self-perceive and/or report their anthropometric characteristics. These findings are of practical value for health professionals and researchers (e.g., nutritionists and exercise physiologists) questionnaires to recreational marathon runners.

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