Validity and Reliability Analysis of the PlotDigitizer Software Program for Data Extraction from Single-Case Graphs

Aydın, Orhan; Yassikaya, Muhammed Yasin

doi:10.1007/s40614-021-00284-0

Cited by 62 publications

(37 citation statements)

References 28 publications

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“…Screenshots of each tier (AB phase) in MB studies that met the data sample criteria were taken and stored on a computer. Data in the graphs were digitized using PlotDigitizer (http://plotdigitizer.sourceforge.net/), which is a software program with high accuracy and reliability in digitizing single‐case graphs (Aydin & Yassikaya, 2022). After digitizing, decimal numbers were rounded to integers by looking at each graph.…”

Section: Methodsmentioning

confidence: 99%

Performance criteria‐based effect size (PCES) measurement of single‐case experimental designs: A real‐world data study

Aydın

Tanious

2022

J of App Behav Analysis

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Visual analysis and nonoverlap-based effect sizes are predominantly used in analyzing single case experimental designs (SCEDs). Although they are popular analytical methods for SCEDs, they have certain limitations. In this study, a new effect size calculation model for SCEDs, named performance criteria-based effect size (PCES), is proposed considering the limitations of 4 nonoverlap-based effect size measures, widely accepted in the literature and that blend well with visual analysis. In the field test of PCES, actual data from published studies were utilized, and the relations between PCES, visual analysis, and the 4 nonoverlap-based methods were examined. In determining the data to be used in the field test, 1,052 tiers (AB phases) were identified from 6 journals. The results revealed a weak or moderate relation between PCES and nonoverlap-based methods due to its focus on performance criteria. Although PCES has some weaknesses, it promises to eliminate the causes that may create issues in nonoverlap-based methods, using quantitative data to determine socially important changes in behavior and to complement visual analysis.

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Section: Methodsmentioning

confidence: 99%

Performance criteria‐based effect size (PCES) measurement of single‐case experimental designs: A real‐world data study

Aydın

Tanious

2022

J of App Behav Analysis

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“…As noted in recent reviews, the use of Plot Digitizer software to extract data from figures and graphs has high interrater reliability, and is more accurate than traditional methods. 29 , 30 If standard errors (SEs) or confidence intervals (CIs) were reported for mean scores, they were converted to SDs using the equations:…”

Section: Methodsmentioning

confidence: 99%

Effects of non-invasive brain stimulation in dystonia: a systematic review and meta-analysis

Morrison-Ham

Clark

Ellis

et al. 2022

Ther Adv Neurol Disord

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Background: Deep brain stimulation is a highly effective treatment of dystonia but is invasive and associated with risks, such as intraoperative bleeding and infections. Previous research has used non-invasive brain stimulation (NIBS) in an attempt to alleviate symptoms of dystonia. The results of these studies, however, have been variable, leaving efficacy unclear. Objectives: This study aimed to evaluate the effects of NIBS on symptoms of dystonia and determine whether methodological characteristics are associated with variability in effect size. Methods: Web of Science, Embase, and MEDLINE Complete databases were searched for articles using any type of NIBS as an intervention in dystonia patients, with changes in dystonia symptoms the primary outcome of interest. Results: Meta-analysis of 27 studies demonstrated a small effect size for NIBS in reducing symptoms of dystonia (random-effects Hedges’ g = 0.21, p = .002). Differences in the type of NIBS, type of dystonia, and brain region stimulated had a significant effect on dystonia symptoms. Meta-regression revealed that 10 sessions of active stimulation and the application of concurrent motor training programs resulted in significantly larger mean effect sizes. Conclusion: NIBS has yielded small improvements to dystonic symptoms, but effect sizes depended on methodological characteristics, with more sessions of stimulation producing a larger response. Future research should further investigate the application of NIBS parallel to motor training, in addition to providing a greater quantity of sessions, to help define optimal parameters for NIBS protocols in dystonia. Registration: PROSPERO 2020, CRD42020175944.

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“…Methane production data of previous studies were digitized from scanned plots of methane production curves using Plot Digitizer 38 . The data from the logarithmic phase of methane accumulation curve were used for the calculation of the maximum specific methane production rate (μ max ) and methane doubling time (G) as follows: 39…”

Section: Calculation Of the Methane Productionmentioning

confidence: 99%

Non-syntrophic methanogenic hydrocarbon degradation by an archaeal species

Zhou

Zhang

Liu

et al. 2021

Nature

119

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The methanogenic degradation of oil hydrocarbons can proceed through syntrophic partnerships of hydrocarbon-degrading bacteria and methanogenic archaea [1][2][3] . However, recent culture-independent studies have suggested that the archaeon 'Candidatus Methanoliparum' alone can combine the degradation of long-chain alkanes with methanogenesis 4,5 . Here we cultured Ca. Methanoliparum from a subsurface oil reservoir. Molecular analyses revealed that Ca. Methanoliparum contains and overexpresses genes encoding alkyl-coenzyme M reductases and methyl-coenzyme M reductases, the marker genes for archaeal multicarbon alkane and methane metabolism. Incubation experiments with different substrates and mass spectrometric detection of coenzyme-M-bound intermediates confirm that Ca. Methanoliparum thrives not only on a variety of long-chain alkanes, but also on n-alkylcyclohexanes and n-alkylbenzenes with long n-alkyl (C ≥13 ) moieties. By contrast, short-chain alkanes (such as ethane to octane) or aromatics with short alkyl chains (C ≤12 ) were not consumed. The wide distribution of Ca. Methanoliparum 4-6 in oil-rich environments indicates that this alkylotrophic methanogen may have a crucial role in the transformation of hydrocarbons into methane.In subsurface oil reservoirs and marine oil seep sediments, microorganisms use hydrocarbons as a source of energy and carbon 7,8 . The microorganisms preferentially consume alkanes, cyclic and aromatic compounds, leaving an unresolved complex mixture as residue and thereby altering the quality of the oil 7,8 . In the absence of sulfate, microorganisms couple anaerobic hydrocarbon degradation to methane formation 1,9,10 . This reaction was originally demonstrated by Zengler et al 2 as methanogenic 'microbial alkane cracking', and a large number of studies have shown that it can be performed in syntrophic interactions of bacteria and archaea 11 . In this syntrophy, the bacteria ferment the oil to acetate, carbon dioxide and hydrogen, while hydrogenotrophic and/or acetotrophic methanogenic archaea use the products for methanogenesis 1,2,11 .Diverse anaerobic hydrocarbon activation mechanisms exist, including the well-studied fumarate addition pathway catalysed by glycyl radical enzymes 12 . This mechanism is widespread among bacteria that thrive on alkanes of various chain lengths and other hydrocarbons 12,13 . By contrast, several archaeal lineages activate gaseous alkanes with the help of a specific type of methyl-coenzyme M reductase (MCR), an enzyme that was originally described to catalyse the reduction of methyl-coenzyme M (methyl-CoM) to methane in methanogens 14 . Anaerobic methanotrophic archaea use canonical MCRs to activate methane into methyl-CoM, which is then oxidized to CO 2 . Short-chain alkane-oxidizing archaea contain divergent variants of this enzyme, which are known as alkyl-CoM reductases (ACRs). Analogous to the methane-activating MCR, ACRs activate multicarbon alkanes to form CoM-bound alkyl units [15][16][17] . The cultured alkane-oxidizing archaea oxidize sho...

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Validity and Reliability Analysis of the PlotDigitizer Software Program for Data Extraction from Single-Case Graphs

Cited by 62 publications

References 28 publications

Performance criteria‐based effect size (PCES) measurement of single‐case experimental designs: A real‐world data study

Performance criteria‐based effect size (PCES) measurement of single‐case experimental designs: A real‐world data study

Effects of non-invasive brain stimulation in dystonia: a systematic review and meta-analysis

Non-syntrophic methanogenic hydrocarbon degradation by an archaeal species

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