Attrition in developmental psychology

2016 ◽  
Vol 41 (1) ◽  
pp. 143-153 ◽  
Author(s):  
Jody S. Nicholson ◽  
Pascal R. Deboeck ◽  
Waylon Howard
Keyword(s):  
Missing Data ◽  
Best Practices ◽  
Developmental Psychology ◽  
American Psychological Association ◽  
Simulated Data ◽  
Drop Out ◽  
Sufficient Information ◽  
Quality Of Reporting ◽  
Reporting Practices

Inherent in applied developmental sciences is the threat to validity and generalizability due to missing data as a result of participant drop-out. The current paper provides an overview of how attrition should be reported, which tests can examine the potential of bias due to attrition (e.g., t-tests, logistic regression, Little's MCAR test, sensitivity analysis), and how it is best corrected through modern missing data analyses. To amend this discussion of best practices in managing and reporting attrition, an assessment of how developmental sciences currently handle attrition was conducted. Longitudinal studies ( n = 541) published from 2009–2012 in major developmental journals were reviewed for attrition reporting practices and how authors handled missing data based on recommendations in the Publication Manual of the American Psychological Association (APA, 2010). Results suggest attrition reporting is not following APA recommendations, quality of reporting did not improve since the APA publication, and a low proportion of authors provided sufficient information to convey that data properly met the MAR assumption. An example based on simulated data demonstrates bias that may result from various missing data mechanisms in longitudinal data, the utility of auxiliary variables for the MAR assumption, and the need for viewing missingness along a continuum from MAR to MNAR.

Estimating the effect of treatment on quality of life in the presence of missing data due to drop-out and death

1998 ◽  
Vol 7 (6) ◽  
pp. 487-494 ◽  
Author(s):  
J. M. Raboud ◽  
J. Singer ◽  
A. Thorne ◽  
M. T. Schechter ◽  
S. D. Shafran
Keyword(s):  
Quality Of Life ◽  
Missing Data ◽  
Drop Out ◽  
Effect Of Treatment

scholarly journals Aspects of Data Quality in Psychology: Missing Data and Aberrant Responses

2021 ◽  
Author(s):  
Maxwell Hong ◽  
Matt Carter ◽  
Cheyeon Kim ◽  
Ying Cheng
Keyword(s):  
Missing Data ◽  
Data Quality ◽  
Developmental Psychology ◽  
Data Preprocessing ◽  
Self Report ◽  
Listwise Deletion ◽  
The Social ◽  
Address Data ◽  
Missing Data Treatment

Data preprocessing is an integral step prior to analyzing data in the social sciences. The purpose of this article is to report the current practices psychological researchers use to address data preprocessing or quality concerns with a focus on issues pertaining to aberrant responses and missing data in self report measures. 240 articles were sampled from four journals: Psychological Science, Journal of Personality and Social Psychology, Developmental Psychology, and Abnormal Psychology from 2012 to 2018. We found that nearly half of the studies did not report any missing data treatment (111/240; 46.25%) and if they did, the most common approach to handle missing data was listwise deletion (71/240; 29.6%). Studies that remove data due to missingness removed, on average, 12% of the sample. We also found that most studies do not report any methodology to address aberrant responses (194/240; 80.83%). For studies that reported issues with aberrant responses, a study would classify 4% of the sample, on average, as suspect responses. These results suggest that most studies are either not transparent enough about their data preprocessing steps or maybe leveraging suboptimal procedures. We outline recommendations for researchers to improve the transparency and/or the data quality of their study.

scholarly journals Self-Harm and Suicide Coverage in Sri Lankan Newspapers

Crisis ◽  
2019 ◽  
Vol 40 (1) ◽  
pp. 54-61 ◽  
Author(s):  
Jane Brandt Sørensen ◽  
Melissa Pearson ◽  
Martin Wolf Andersen ◽  
Manjula Weerasinghe ◽  
Manjula Rathnaweera ◽  
...  
Keyword(s):  
Help Seeking ◽  
Reporting Quality ◽  
Sri Lankan ◽  
Quality Of Reporting ◽  
Reporting Practices ◽  
Short Period ◽  
Self Harm ◽  
The Individual ◽  
English Articles

Abstract. Background: Irresponsible media reporting may influence suicidal behavior. Adherence to guidelines for responsible reporting of suicide has not been examined in Sri Lanka in recent times. Aims: To examine the quality of reporting on self-harm and suicide in Sri Lankan newspapers and compare the quality between Sinhala and English newspapers. Method: From December 1, 2014 to January 31, 2015, 407 editions of newspapers were screened. Reporting quality was measured using the PRINTQUAL tool. Results: We identified 68 articles covering an episode of self-harm or suicide (42 Sinhala and 26 English). The majority of articles were noncompliant with guidelines for sensitive reporting. Indicators of noncompliance included that newspaper articles frequently reported method in the headline (53%), included detailed characteristics of the individual (100%), used insensitive language (58% of English articles), and attributed a single-factor cause to the self-harm (52%). No information about help-seeking was included. Limitations: The study involved a relatively short period of data collection. Including social media, Tamil language newspapers, and online publications would have provided additional understanding of reporting practices. Conclusion: The majority of Sri Lankan newspapers did not follow the principles of good reporting, indicating a need for further training of journalists.

Quality of Reporting of Harms in the NCI Sponsored Phase III Hematological Malignancies Trials.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 292-292
Author(s):  
Heloisa P. Soares ◽  
Ambuj Kumar ◽  
Benjamin Djulbegovic
Keyword(s):  
Clinical Trials ◽  
Survival Data ◽  
Hematological Malignancy ◽  
Meta Analysis ◽  
Drop Out ◽  
Phase Iii ◽  
Accurate Information ◽  
Power Calculation ◽  
Quality Of Reporting

Abstract Background: To make informed decisions, patients and physicians need accurate information both on treatment benefits and harms. However, reports of clinical trials typically focus on description of benefits only. Research supported by the NCI account almost for 100% of all publicly sponsored phase III trials in the US, and is widely considered as the most important for advancement of treatment against cancer. Therefore, it is important to assess the quality of reporting of treatment-related mortality (TRM) and morbidity (TRMorb) in this setting. Methods: We evaluated all randomized controlled trials (RCTs) that have been conducted by six NCI sponsored cooperative oncology groups (COGs). We included all trials that were completed by 2002. Here we focus on hematological malignancy trials. Data related to TRM and TRMorb were extracted from publications that reported benefits (i.e. survival or event-free survival). Data were pooled using meta-analytic techniques to assess if the harms were worse in experimental vs. standard treatments. Results: We evaluated,114 hematological-malignancy trials. Seventy-nine trials studied leukemias, 32 lymphomas and 3 either multiple myeloma or myelodysplastic syndrome. Quality of reporting for the most important methodological domains (such as randomization methodology, power calculation, drop-out rates, use of intention-to-treat analysis) was high. Data related to TRM were extractable from 41 trials (36%) only. Overall, TRM accounted for less than 5% of all deaths and was shown to be significantly higher in patients allocated to innovative treatments [Odds ratio 1.93: 99%CI (1.11–1.76)]. TRM was similar according to the type of hematological malignancy or COG. Treatment-related morbidity data were reported in different non-standardized formats; therefore, it was not possible to perform a meta-analysis to give an accurate assessment of TRMorb in experimental and conventional treatment arms. Conclusion: Treatment-related harms have been inadequately reported even in the currently best available research. Given the fact, that the users of research evidence can only rely on the available published reports, the NCI should urgently improve the requirment for the standards of reporting of clinical trials it funds.

scholarly journals Evaluating the Reporting Quality of Researcher-Developed Alphabet Knowledge Measures: How Transparent and Replicable Is It?

2021 ◽  
Vol 12 ◽  
Author(s):  
Sherri L. Horner ◽  
Sharon A. Shaffer
Keyword(s):  
Data Collection ◽  
American Psychological Association ◽  
American Educational Research Association ◽  
Reporting Quality ◽  
Journal Editor ◽  
Research Association ◽  
Quality Of Reporting ◽  
Alphabet Knowledge ◽  
The Impact

The American Educational Research Association and American Psychological Association published standards for reporting on research. The transparency of reporting measures and data collection is paramount for interpretability and replicability of research. We analyzed 57 articles that assessed alphabet knowledge (AK) using researcher-developed measures. The quality of reporting on different elements of AK measures and data collection was not related to the journal type nor to the impact factor or rank of the journal but rather seemed to depend on the individual author, reviewers, and journal editor. We propose various topics related to effective reporting of measures and data collection methods that we encourage the early childhood and literacy communities to discuss.

scholarly journals Measuring the reproducibility and quality of Hi-C data

2017 ◽  
Author(s):  
Galip Gürkan Yardımcı ◽  
Hakan Ozadam ◽  
Michael E.G. Sauria ◽  
Oana Ursu ◽  
Koon-Kiu Yan ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Best Practices ◽  
Correlation Analysis ◽  
Quality Assessment ◽  
Simulated Data ◽  
Depth Resolution ◽  
Quality Measures ◽  
Noise Levels ◽  
Simple Correlation

AbstractHi-C is currently the most widely used assay to investigate the 3D organization of the genome and to study its role in gene regulation, DNA replication, and disease. However, Hi-C experiments are costly to perform and involve multiple complex experimental steps; thus, accurate methods for measuring the quality and reproducibility of Hi-C data are essential to determine whether the output should be used further in a study. Using real and simulated data, we profile the performance of several recently proposed methods for assessing reproducibility of population Hi-C data, including HiCRep, GenomeDISCO, HiC-Spector and QuASAR-Rep. By explicitly controlling noise and sparsity through simulations, we demonstrate the deficiencies of performing simple correlation analysis on pairs of matrices, and we show that methods developed specifically for Hi-C data produce better measures of reproducibility. We also show how to use established (e.g., ratio of intra to interchromosomal interactions) and novel (e.g., QuASAR-QC) measures to identify low quality experiments. In this work, we assess reproducibility and quality measures by varying sequencing depth, resolution and noise levels in Hi-C data from 13 cell lines, with two biological replicates each, as well as 176 simulated matrices. Through this extensive validation and benchmarking of Hi-C data, we describe best practices for reproducibility and quality assessment of Hi-C experiments. We make all software publicly available at http://github.com/kundajelab/3DChromatin_ReplicateQC to facilitate adoption in the community.

PROFESSIONAL TRAINING OF ELECTRONICS ENGINEERS: APPLYING US EXPERICENCE TO UKRAINAN HIGHER EDUCATION INSTITUTIONS

2020 ◽  
pp. 80-85
Author(s):  
Olha Pavlenko
Keyword(s):  
Higher Education ◽  
Education Research ◽  
Best Practices ◽  
Cost Reduction ◽  
Professional Training ◽  
Higher Education Institutions ◽  
Academic Staff ◽  
Research And Innovation ◽  
Current State

The article discusses the current state of professional training of engineers, in particular, electronics engineers in Ukrainian higher education institutions (HEIs) and explores best practices from US HEIs. The research outlines the features of professional training of electronics engineers and recent changes in Ukrainian HEIs. Such challenges for Ukrainian HEIs as lack of collaboration between higher education and science with industry, R&D cost reduction for HEIs, and downsizing the research and academic staff, the disparity between the available quality of human capital training and the demanded are addressed. The study attempts to identify successful practices of US HEIs professional training of engineers in order to suggest potential improvements in education, research, and innovation for training electronics engineers in Ukraine.

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