scholarly journals Six solutions for more reliable infant research

2021 ◽  
Author(s):  
Krista Byers-Heinlein ◽  
Christina Bergmann ◽  
Victoria Savalei
Keyword(s):  
Effect Size ◽  
Statistical Power ◽  
Infant Development ◽  
Measurement Tool ◽  
Measurement Reliability ◽  
Size Measurement ◽  
Infant Research ◽  
Data Points ◽  
Effect Size Measurement ◽  
The Relationship

Infant research is often underpowered, undermining the robustness and replicability of our findings. Improving the reliability of infant measures offers a solution for increasing statistical power independent of sample size. Here, we discuss two senses of the term reliability in the context of infant research: reliable (large) effects and reliable measures. We examine the circumstances under which effects are strongest and measures are most reliable, and provide simulations to illustrate the relationship between effect size, measurement reliability, and statistical power. We then present six concrete solutions for improving measurement in infant research: (1) routinely estimating and reporting the effect size and measurement reliability of infant tasks, (2) selecting the best measurement tool, (3) developing better infant paradigms, (4) collecting more data points per infant, (5) excluding unreliable data from analysis, and (6) conducting more sophisticated data analyses. Deeper consideration of measurement in infant research will improve our ability to study infant development.

scholarly journals Social Skills and Coexistence in the Virtual Classroom in University Students

2021 ◽  
Vol 11 (1) ◽  
pp. 5969-5982
Author(s):  
Dennis Arias- Chávez ◽  
Mitchell Alberto Alarcón Diaz ◽  
Liset Sulay Rodriguez Baca ◽  
Segundo Pérez Saavedra
Keyword(s):  
Social Skills ◽  
University Students ◽  
Effect Size ◽  
Statistical Power ◽  
Pearson Correlation ◽  
Virtual Classroom ◽  
Weak Correlation ◽  
The Social ◽  
The Relationship ◽  
Very High

The purpose of this study was to determine the relationship between social skills and coexistence in the virtual classroom of students in intermediate cycles of the four branches of a Peruvian university. The population was 11,700 students from the fourth to the seventh cycle, from which a sample of 390 students was extracted. The instruments applied were: the Social Skills Scale (EHB) and the Virtual Classroom Coexistence Scale (ECAV). The results show that there is a direct and low relationship between social skills and coexistence in the virtual classroom given that the Pearson correlation is .240, the effect size is 0.4969909 and the statistical power is 1.000. It is concluded that there is a very weak correlation; however, the effect size is large and the statistical power is very high.

How to Detect Publication Bias in Psychological Research

2019 ◽  
Vol 227 (4) ◽  
pp. 261-279 ◽  
Author(s):  
Frank Renkewitz ◽  
Melanie Keiner
Keyword(s):  
Publication Bias ◽  
Effect Size ◽  
Statistical Power ◽  
Type I Error ◽  
Psychological Research ◽  
Type I ◽  
True Effect Size ◽  
Questionable Research Practices ◽  
True Effect ◽  
Meta Analyses

Abstract. Publication biases and questionable research practices are assumed to be two of the main causes of low replication rates. Both of these problems lead to severely inflated effect size estimates in meta-analyses. Methodologists have proposed a number of statistical tools to detect such bias in meta-analytic results. We present an evaluation of the performance of six of these tools. To assess the Type I error rate and the statistical power of these methods, we simulated a large variety of literatures that differed with regard to true effect size, heterogeneity, number of available primary studies, and sample sizes of these primary studies; furthermore, simulated studies were subjected to different degrees of publication bias. Our results show that across all simulated conditions, no method consistently outperformed the others. Additionally, all methods performed poorly when true effect sizes were heterogeneous or primary studies had a small chance of being published, irrespective of their results. This suggests that in many actual meta-analyses in psychology, bias will remain undiscovered no matter which detection method is used.

The Relationship Between Immorality and Cleansing

2018 ◽  
Vol 49 (5) ◽  
pp. 303-309 ◽  
Author(s):  
Jedidiah Siev ◽  
Shelby E. Zuckerman ◽  
Joseph J. Siev
Keyword(s):  
Effect Size ◽  
Meta Analysis ◽  
Weighted Mean ◽  
The Relationship

Abstract. In a widely publicized set of studies, participants who were primed to consider unethical events preferred cleansing products more than did those primed with ethical events ( Zhong & Liljenquist, 2006 ). This tendency to respond to moral threat with physical cleansing is known as the Macbeth Effect. Several subsequent efforts, however, did not replicate this relationship. The present manuscript reports the results of a meta-analysis of 15 studies testing this relationship. The weighted mean effect size was small across all studies (g = 0.17, 95% CI [0.04, 0.31]), and nonsignificant across studies conducted in independent laboratories (g = 0.07, 95% CI [−0.04, 0.19]). We conclude that there is little evidence for an overall Macbeth Effect; however, there may be a Macbeth Effect under certain conditions.

Identifying Physico-Chemical Laws from the Robotically Collected Data

2019 ◽  
Author(s):  
Liwei Cao ◽  
Danilo Russo ◽  
Vassilios S. Vassiliadis ◽  
Alexei Lapkin
Keyword(s):  
Experimental Data ◽  
Numerical Models ◽  
Predictor Variable ◽  
Physical Models ◽  
Training Data ◽  
Mixed Integer ◽  
Physico Chemical ◽  
Data Points ◽  
Future Work ◽  
The Relationship

<p>A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor variables and training data points. The globally optimal search was extended to identify physical models and to cope with noise in the experimental data predictor variable. The methodology was coupled with the collection of experimental data in an automated fashion, and was proven to be successful in identifying the correct physical models describing the relationship between the shear stress and shear rate for both Newtonian and non-Newtonian fluids, and simple kinetic laws of reactions. Future work will focus on addressing the limitations of the formulation presented in this work, by extending it to be able to address larger complex physical models.</p><p><br></p>

Exploring power in response inhibition tasks using the bootstrap: The impact of number of participants, number of trials, effect magnitude, and study design

2019 ◽  
Author(s):  
Curtis David Von Gunten ◽  
Bruce D Bartholow
Keyword(s):  
Study Design ◽  
Effect Size ◽  
Statistical Power ◽  
Bootstrap Sampling ◽  
Reliable Measure ◽  
Internal Reliability ◽  
The Impact ◽  
Power Analyses ◽  
Effect Magnitude

A primary psychometric concern with laboratory-based inhibition tasks has been their reliability. However, a reliable measure may not be necessary or sufficient for reliably detecting effects (statistical power). The current study used a bootstrap sampling approach to systematically examine how the number of participants, the number of trials, the magnitude of an effect, and study design (between- vs. within-subject) jointly contribute to power in five commonly used inhibition tasks. The results demonstrate the shortcomings of relying solely on measurement reliability when determining the number of trials to use in an inhibition task: high internal reliability can be accompanied with low power and low reliability can be accompanied with high power. For instance, adding additional trials once sufficient reliability has been reached can result in large gains in power. The dissociation between reliability and power was particularly apparent in between-subject designs where the number of participants contributed greatly to power but little to reliability, and where the number of trials contributed greatly to reliability but only modestly (depending on the task) to power. For between-subject designs, the probability of detecting small-to-medium-sized effects with 150 participants (total) was generally less than 55%. However, effect size was positively associated with number of trials. Thus, researchers have some control over effect size and this needs to be considered when conducting power analyses using analytic methods that take such effect sizes as an argument. Results are discussed in the context of recent claims regarding the role of inhibition tasks in experimental and individual difference designs.

scholarly journals Development of Postpartum Depression in Pregnant Women with Preeclampsia: A Retrospective Study

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Li Chen ◽  
Xiaodan Wang ◽  
Qian Ding ◽  
Nan Shan ◽  
Hongbo Qi
Keyword(s):  
Postpartum Depression ◽  
Infant Development ◽  
Survey Methodology ◽  
Depression Scale ◽  
Bivariate Analysis ◽  
Increased Risk ◽  
Normal Women ◽  
Medical University ◽  
Support Methods ◽  
The Relationship

Background. Postpartum depression (PPD) and preeclampsia (PE) are both common diseases in obstetrics that affect maternal health and infant development. However, the relationship between the two diseases still requires clarification. Objective. The purpose of this study was to (1) determine the incidence rate of PPD in patients with PE and (2) identify the association between the prevalence of PPD and the severity of PE. Methods. We conducted a retrospective analysis of women with and without PE who delivered between January 1, 2017, and August 30, 2018, in the First Affiliated Hospital of Chongqing Medical University. We used a questionnaire survey methodology that included the Edinburgh Postnatal Depression Scale (EPDS) to test the influence of PE on the development of new-onset PPD in the 6 weeks after delivery. We determined PPD based on a score ≥10 on the EPDS. Bivariate analysis was used to compare data between the two groups. Results. A total of 180 women participated in this study. Thirty-five people screened positive for PPD, while the remaining 145 screened negative. The prevalence of PPD was 26.67% (24/90) in patients with PE, which was two times the prevalence in normal women (12.22%). Multiple logistic regression showed that women who had PE had nearly 3-fold increased odds of PPD compared to normal women and the risk of PPD increased with the aggravation of PE. Patients with severe PE had a more than 4-fold increased risk of screening positive for PPD. Conclusion. PE was independently associated with PPD. Furthermore, the risk of PPD seemed to increase with the aggravation of PE. Thus, additional prevention efforts and support methods should be provided for women with PE to reduce the incidence of PPD.

Factors Associated with Maternal Opinion of Infant Development—Clues to the Vulnerable Child?

PEDIATRICS ◽  
1982 ◽  
Vol 69 (5) ◽  
pp. 537-543
Author(s):  
Marie C. McCormick ◽  
Sam Shapiro ◽  
Barbara Starfield
Keyword(s):  
Birth Weight ◽  
Infant Development ◽  
Infant Health ◽  
Subsequent Development ◽  
First Year ◽  
Factors Associated ◽  
Slow Development ◽  
First Year Of Life ◽  
Relationship Of ◽  
The Relationship

A mother's expectations about the development of her infant have been found to be a strong determinant of child development, but little is known about the factors that may affect maternal assessment of development. In this study, the relationship of the mother's opinion of the development of her infant with several sociodemographic, antenatal, intrapartum, and infant health variables was examined for a large sample of 1-year-old infants for whom gross motor observations were also obtained at the time of the interview. Among those observed to be developing at an appropriate rate, 4.0% were perceived by their mothers as developing more slowly than the mothers considered normal; among infants developing more slowly, 28.6% were considered to be developing slowly by their mothers. In both groups, the major determinants of maternal opinion of slow development concerned the infant's health: low birth weight, congenital anomalies regardless of severity, hospitalization during the first year of life, and high ambulatory care use. These results indicate that maternal perception of infant development may not reflect the infant's level, but past or present illness, and raise questions about the influence of infant health on maternal-infant interactions and the effect of such interactions on subsequent development in the child.

Field Assisted Sintering Technology (FAST) Model for Prediction of Final Properties

2010 ◽  
Author(s):  
Rajiv Paul ◽  
Anil K. Kulkarni ◽  
Jogender Singh
Keyword(s):  
Electrical Breakdown ◽  
Extensive Literature ◽  
Heating Rates ◽  
Predictive Tool ◽  
Simultaneous Application ◽  
Plasma Sintering ◽  
Spark Plasma ◽  
Data Points ◽  
Field Assisted Sintering ◽  
The Relationship

Sintering is the process of making materials from powder form by heating the powder below its melting point until the particles fuse to each other. Field assisted sintering technology (FAST), also sometimes known as spark plasma sintering (SPS), uses a pulsed and/or continuous electric current along with the simultaneous application of compressive pressure which leads to extremely high heating rates and short processing durations. A high relative density and small grain size promote superior properties such as greater hardness and electrical breakdown. Hence, selection of the proper sintering parameters is of paramount importance and a predictive model would be extremely useful in narrowing the range of experimental parameters. This will drastically reduce the number of extra attempts at obtaining certain properties in a material and save experimentation time, effort and material to name a few. Four of the most important FAST parameters: target temperature, holding time, heating rate and initial particle size, have been reviewed to assess their effect on the densification, hardening and grain growth of Alumina, Copper, Silicon Carbide, Tungsten and Tungsten Carbide through extensive literature survey. The relationship between each has been incorporated in a Microsoft Excel program which acts as a predictive tool to determine an estimate of the final properties based on the initial parameters chosen. This is done by curve fitting a polynomial onto the existing data points as closely as possible and using the polynomial to obtain final properties as a function of the initial parameters. The model was verified against an existing paper which sought to obtain the optimum sintering parameters for Copper. While the actual experimentation range was 400°C to 800°C, the program would have suggested a much narrower range from 650°C to 800°C and hence saved unnecessary additional efforts.

Using confidence intervals to estimate the response of salmon populations (Oncorhynchus spp.) to experimental habitat alterations

2005 ◽  
Vol 62 (12) ◽  
pp. 2716-2726 ◽  
Author(s):  
Michael J Bradford ◽  
Josh Korman ◽  
Paul S Higgins
Keyword(s):  
Confidence Intervals ◽  
Effect Size ◽  
Null Hypothesis ◽  
Statistical Power ◽  
Habitat Restoration ◽  
Coho Salmon ◽  
Fish Habitat ◽  
Monitoring Program ◽  
Considerable Uncertainty ◽  
Monitoring Programs

There is considerable uncertainty about the effectiveness of fish habitat restoration programs, and reliable monitoring programs are needed to evaluate them. Statistical power analysis based on traditional hypothesis tests are usually used for monitoring program design, but here we argue that effect size estimates and their associated confidence intervals are more informative because results can be compared with both the null hypothesis of no effect and effect sizes of interest, such as restoration goals. We used a stochastic simulation model to compare alternative monitoring strategies for a habitat alteration that would change the productivity and capacity of a coho salmon (Oncorhynchus kisutch) producing stream. Estimates of the effect size using a freshwater stock–recruit model were more precise than those from monitoring the abundance of either spawners or smolts. Less than ideal monitoring programs can produce ambiguous results, which are cases in which the confidence interval includes both the null hypothesis and the effect size of interest. Our model is a useful planning tool because it allows the evaluation of the utility of different types of monitoring data, which should stimulate discussion on how the results will ultimately inform decision-making.

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