scholarly journals Erratum

2016 ◽  
Vol 53 (5) ◽  
pp. NP1-NP1
Keyword(s):  
Cognitive Load ◽  
Sample Size ◽  
Degrees Of Freedom ◽  
Health And Safety ◽  
Marketing Research ◽  
Initial Sample ◽  
Safety Concerns ◽  
Main Effect

White, Katherine, Lily Lin, Darren W. Dahl, and Robin J. B. Ritchie (2016), “When Do Consumers Avoid Imperfections? Superficial Packaging Damage as a Contamination Cue,” Journal of Marketing Research, 53 (February), 110–23. (Original DOI: 10.1509/jmr.12.0388 ) The following reporting errors have been noted in this article. These errors were clerical only, and the changes do not affect the data patterns or significance of the results in any way. Study 1, page 113 The numerator degrees of freedom for the interaction should be 2. At the end of the last full paragraph, the text should read: “The interaction qualified a significant main effect for type of package damage (F(2, 139) = 4.90, p < .05) and a marginal main effect for cognitive load (F(1, 139) = 3.36, p < .07).” Study 2, page 115 The degrees of freedom should be 130. The text should read: “Results revealed a main effect for packaging damage (t(130) = 5.49, p < .001; b = −.561) and the anticipated three-way interaction (t(130) = 2.24, p < .03; b = −.286; see Figure 2).” Study 4, page 116 The numerator degrees of freedom was omitted in one sentence. The text should read: “As we predicted, packaging appearance predicted both contamination perceptions (F(2, 150) = 4.17, p < .05) and health and safety concerns (F(2, 150) = 3.41, p < .05; see Table 1).” Study 5, page 118 The initial sample size is 200 participants. The text should say: “Those who failed to properly complete the cognitive load task were removed from the analyses (9.5% of the sample, leaving 181 participants).”

Addressing Health And Safety Concerns For Tradeswomen In The Construction Industry

2017 ◽  
Author(s):  
Hannah M. Curtis ◽  
Hendrika Meischke ◽  
Nancy Simcox ◽  
Sarah Laslett ◽  
Noah Seixas
Keyword(s):  
Construction Industry ◽  
Health And Safety ◽  
Safety Concerns

scholarly journals Evaluation of Self-Reported Agricultural Tasks, Safety Concerns, and Health and Safety Behaviors of Young Adults in U.S. Collegiate Agricultural Programs

Safety ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 44
Author(s):  
J. L. Gibbs ◽  
K. Walls ◽  
C. Sheridan ◽  
D. Sullivan ◽  
M. Cheyney ◽  
...  
Keyword(s):  
Young Adults ◽  
Healthcare Providers ◽  
Health And Safety ◽  
Safety Behaviors ◽  
Medical Provider ◽  
Near Misses ◽  
Safety Issues ◽  
Agricultural Health ◽  
Safety Concerns ◽  
Agricultural Programs

Young adults enrolled in collegiate agricultural programs are a critical audience for agricultural health and safety training. Understanding the farm tasks that young adults engage in is necessary for tailoring health and safety education. The project analyzed evaluation survey responses from the Gear Up for Ag Health and Safety™ program, including reported agricultural tasks, safety concerns, frequency of discussing health and safety concerns with healthcare providers, safety behaviors, and future career plans. The most common tasks reported included operation of machinery and grain-handling. Most participants intended to work on a family-owned agricultural operation or for an agribusiness/cooperative following graduation. Reported safety behaviors (hearing protection, eye protection, and sunscreen use when performing outdoor tasks) differed by gender and education type. Male community college and university participants reported higher rates of “near-misses” and crashes when operating equipment on the roadway. One-third of participants reported discussing agricultural health and safety issues with their medical provider, while 72% were concerned about the health and safety of their family and co-workers in agriculture. These findings provide guidance for better development of agricultural health and safety programs addressing this population—future trainings should be uniquely tailored, accounting for gender and educational differences.

Evaluating the Safety of Shared-Use Paths

2005 ◽  
Vol 1939 (1) ◽  
pp. 99-106 ◽  
Author(s):  
Lisa Aultman-Hall ◽  
Jeffrey LaMondia
Keyword(s):  
Sample Size ◽  
Event Rate ◽  
The Self ◽  
Travel Patterns ◽  
Unit Distance ◽  
Safety Concerns ◽  
Crash Rates ◽  
Incident Rate

The project described in this paper involved the design of a survey of shared-use path safety for use at three facilities in Connecticut in the fall of 2002 and the summer of 2003. The objective was to collect self-reported information on collision and fall events and on travel exposure so that crash rates could be developed. The analysis of the self-reported events and travel patterns provides complementary data that are not available from other sources but are needed to address safety concerns on these facilities. The strengths of this approach include the collection of underreported minor events and the ability to estimate travel exposure and thus allow the estimation of crash rates per unit distance. The sample size of 684 was sufficient only for the development of aggregate crash rates, which suggest that skaters have the highest rates, followed by bicyclists and then pedestrians. The bicycle event rate was three times that of pedestrians, while the rate for skaters was more than six times that for pedestrians. Falls were more frequently reported than collisions, and they were more often associated with an injury. The overall incident rate for each of the three individual facilities was the highest for the path with the highest user volume and highest percentage of skaters and cyclists.

scholarly journals Nanoexposure, Unusual Diseases, and New Health and Safety Concerns

2011 ◽  
Vol 11 ◽  
pp. 1821-1828 ◽  
Author(s):  
Yuguo Song ◽  
Shichuan Tang
Keyword(s):  
Pulmonary Fibrosis ◽  
Lung Injury ◽  
Silica Nanoparticles ◽  
Personal Protective Equipment ◽  
Health And Safety ◽  
Protective Equipment ◽  
Nanoparticle Exposure ◽  
Safety Concerns ◽  
Collaborative Efforts

Accumulating studies in animals have shown that nanoparticles could cause unusual rapid lung injury and extrapulmonary toxicity. Whether exposure of workers to nanoparticles may result in some unexpected damage as seen in animals is still a big concern. We previously reported findings regarding a group of patients exposed to nanoparticles and presenting with an unusual disease. The reported disease was characterized by bilateral chest fluid, pulmonary fibrosis, pleural granuloma, and multiorgan damage and was highly associated with the nanoparticle exposure. To strengthen this association, further information on exposure and the disease was collected and discussed. Our studies show that some kinds of nanomaterials, such as silica nanoparticles and nanosilicates, may be very toxic and even fatal to occupational workers exposed to them without any effective personal protective equipment. More research and collaborative efforts on nanosafety are required in order to prevent and minimize the potential hazards of nanomaterials to humans and the environment.

data a; * significance level; a=0.05; * variance of difference of two observations on the log scale; * sigmaW = within-subjects standard deviation; sigmaW=0.355; s=sqrt(2)*sigmaW; * total number of subjects (needs to be a multiple of 2); n=58; * error degrees of freedom for AB/BA cross-over with n subjects in total; n2=n-2; * ratio = mu_T/mu_R; ratio=1.00; run; data b; set a; * calculate power; t1=tinv(1-a,n-2); t2=-t1; nc1=(sqrt(n))*((log(ratio)-log(0.8))/s); nc2=(sqrt(n))*((log(ratio)-log(1.25))/s); df=(sqrt(n-2))*((nc1-nc2)/(2*t1)); prob1=probt(t1,df,nc1); prob2=probt(t2,df,nc2); answer=prob2-prob1; power=answer*100; run; proc print data=b; run; As an example of using this SAS code, suppose µ = 1, σ = 0.355, α = 0.05 and n = 58. The power (as a percentage) is calculated as 90.4. The required number of subjects to achieve a given power can easily be obtained by trial and error using a selection of values of n. An alternative approach is to use trial and error directly on the sample size n for a given power. For more on this see Phillips (1990) and Diletti et al. (1991), for example. 7.4 Individual bioequivalence As noted in Section 7.1, individual bioequivalence (IBE) is a criterion for deciding if a patient who is currently being treated with R can be

2003 ◽  
pp. 362-362
Keyword(s):  
Standard Deviation ◽  
Sample Size ◽  
Degrees Of Freedom ◽  
Trial And Error ◽  
Significance Level ◽  
Individual Bioequivalence ◽  
Alternative Approach ◽  
Within Subjects ◽  
Log Ratio ◽  
Selection Of

scholarly journals The Science of Technology and Human Behavior: Standards, Old and New

2017 ◽  
Author(s):  
Malte Elson ◽  
Andrew K Przybylski
Keyword(s):  
Sample Size ◽  
Human Behavior ◽  
Degrees Of Freedom ◽  
Meta Analysis ◽  
Average Power ◽  
P Value ◽  
Test Statistics ◽  
Healthy Sample ◽  
D 20 ◽  
Single Publication

Editorial of the Journal of Media Psychology special issue on "Technology &amp; Human Behavior", and meta-analysis of the empirical research published in JMP since 2008.DATA AVAILABILITYWe were not able to identify a single publication reporting a link to research data in a public repository or the journal’s supplementary materials.STATISTICAL REPORTING ERRORSWe extracted a total of 1036 NHSTs reported in 98 articles. 129 tests were flagged as inconsistent (i.e., reported test statistics and degrees of freedom do not match reported p-values), of which 23 were grossly inconsistent (the reported p-value is &lt;.05 while the recomputed p-value is &gt;.05, or vice-versa). 41 publications reported at least one inconsistent NHST, and 16 publications reported at least one grossly inconsistent NHST. Thus, a substantial proportion of publications in JMP seem to contain inaccurately reported statistical analyses, of which some might affect the conclusions drawn from them.STATISTICAL POWERAs in other fields, surveys tend to have healthy sample sizes apt to reliably detect medium to large relationships between variables. The median sample size for survey studies is 327, allowing researchers to detect small bivariate correlations of r=.1 at 44% power (rs=.3/.5 both &gt; 99%).For (quasi-)experiments, the outlook is a bit different, with a median sample size of 107. Across all types of designs, the median condition size is 30.67. Thus, the average power of experiments published in JMP to detect small differences between conditions (d=.20) is 12% (d=.50 at 49%, d=.80 at 87%).

Discriminant validity assessment in marketing research

2018 ◽  
Vol 61 (2) ◽  
pp. 210-222 ◽  
Author(s):  
Joseph M Matthes ◽  
A Dwayne Ball
Keyword(s):  
Measurement Error ◽  
Sample Size ◽  
Discriminant Validity ◽  
Marketing Research ◽  
Size Measurement ◽  
Artificial Data ◽  
Validity Assessment ◽  
Recommendations For Practice ◽  
Artificial Datasets ◽  
Measurement Validity

Establishing discriminant validity has been a keystone of measurement validity in empirical marketing research for many decades. Without statistically showing that constructs have discriminant validity, contributions to marketing literature are likely to foster the proliferation of constructs that are operationally the same as other constructs already present in the literature, thus leading to confusion in the development of theory. This article addresses this concern by evaluating well-established methods for testing discriminant validity through the simulation of artificial datasets (containing varying levels of correlation between constructs, sample size, measurement error, and distribution skewness). The artificial data are applied to six commonly used approaches for testing the existence of discriminant validity. Results strongly suggest that several methods are much more likely than others to yield accurate assessments of whether discriminant validity exists, especially under specific conditions. Recommendations for practice in the assessment of discriminant validity are suggested.

Health and safety concerns in the paintings conservation studio

2020 ◽  
pp. 761-776
Author(s):  
Monona Rossol ◽  
Mary McGinn ◽  
Joyce H. Townsend
Keyword(s):  
Health And Safety ◽  
Safety Concerns
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