ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients

Kim, Seong Ho

doi:10.5351/csam.2015.22.6.665

Cited by 753 publications

(704 citation statements)

References 20 publications

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“…ROC analyses were computed using pROC, 41 and non-parametric Spearman’s rank-order bivariate and partial correlations were implemented using the ppcor program 43 in R. Individual ROI analyses were computed using IBM SPSS v23.0. 44 In spite of strong directional predictions for all group differences and bivariate relationships, α=.05 two-tailed was used.…”

Section: Methodsmentioning

confidence: 99%

Development of an Objective Autism Risk Index Using Remote Eye Tracking

Frazier

Klingemier

Beukemann

et al. 2016

Journal of the American Academy of Child & Adolescent Psych

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Objective Abnormal eye gaze is a hallmark characteristic of autism spectrum disorder (ASD), and numerous studies have identified abnormal attention patterns in ASD. The primary aim of the present study was to create an objective, eye tracking-based autism risk index. Method In initial and replication studies, children were recruited after referral for comprehensive multidisciplinary evaluation of ASD and subsequently grouped by clinical consensus diagnosis (ASD n=25/15, non-ASD n=20/19 for initial/replication samples). Remote eye tracking was blinded to diagnosis and included multiple stimuli. Dwell times were recorded to each a priori-defined region-of-interest (ROI) and averaged across ROIs to create an autism risk index. Receiver operating characteristic curve analyses examined classification accuracy. Correlations with clinical measures evaluated whether the autism risk index was associated with autism symptom severity independent of language ability. Results In both samples, the autism risk index had high diagnostic accuracy (area under the curve [AUC]=.91 and .85, 95%CIs=.81–.98 and .71–.96), was strongly associated with Autism Diagnostic Observation Schedule–Second Edition (ADOS-2) severity scores (r=.58 and .59, p<.001), and not significantly correlated with language ability (r≤|−.28|, p>.095). Conclusion The autism risk index may be a useful quantitative and objective measure of risk for autism in at-risk settings. Future research in larger samples is needed to cross-validate these findings. If a validated scale for clinical use, this measure could inform clinical judgment regarding ASD diagnosis and track symptom improvements.

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Section: Methodsmentioning

confidence: 99%

Development of an Objective Autism Risk Index Using Remote Eye Tracking

Frazier

Klingemier

Beukemann

et al. 2016

Journal of the American Academy of Child & Adolescent Psych

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“…This selection was based on preliminary partial correlations between our eight a priori selected white matter motor tracts and grip strength after accounting for age (see Table 2). The partial correlations were conducted with the ppcor package in R (Kim 2012). Structural equation model path analyses were conducted using the Latent Variable Analysis (lavaan) package in R (Rosseel 2012).…”

Section: Methodsmentioning

confidence: 99%

Brainstem White Matter Predicts Individual Differences in Manual Motor Difficulties and Symptom Severity in Autism

Travers

Bigler

Tromp

et al. 2015

J Autism Dev Disord

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Mounting evidence suggests that poorer motor skills may be related to more severe autism symptoms. This study investigated if atypical white matter microstructure in the brain mediated the relationship between motor skills and ASD symptom severity. Sixty-seven males with ASD and 42 males with typical development (5-33 years old) completed a diffusion tensor imaging scan and measures of grip strength, finger tapping, and autism symptom severity. Within the ASD group, weaker grip strength predicted more severe autism symptoms. Fractional anisotropy of the brainstem's corticospinal tract predicted both grip strength and autism symptom severity and mediated the relationship between the two. These findings suggest that brainstem white matter may contribute to autism symptoms and grip strength in ASD.

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“…We assessed the correlation coefficients and their statistical significance using ppcor [26], an R package designed for partial correlation analyses. If the decline in score of each assessment instrument exhibited a significant correlation with the percent change in cGMV, the assessment scale was considered a valid monitoring instrument for longitudinal monitoring of AD or aMCI.…”

Section: Methodsmentioning

confidence: 99%

Tracking Cognitive Decline in Amnestic Mild Cognitive Impairment and Early-Stage Alzheimer Dementia: Mini-Mental State Examination versus Neuropsychological Battery

Kim

Byun

et al. 2017

Dement Geriatr Cogn Disord

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Background/Aims: Although the Mini-Mental State Examination (MMSE), Clinical Dementia Rating-Sum of Boxes (CDR-SOB), and neuropsychological batteries are widely used for evaluating cognitive function, it remains elusive which instrument best reflects the longitudinal disease progression in amnestic mild cognitive impairment (aMCI) and probable Alzheimer disease (AD). We investigated whether changes in these three instruments over time correlate with loss of cortical gray matter volume (cGMV). Methods: We retrospectively investigated 204 patients (aMCI, n = 114; AD, n = 90) who had undergone MMSE, CDR-SOB, the dementia version of the Seoul Neuropsychological Screening Battery (SNSB-D), and 3-dimensional T1-weighted magnetic resonance images at least twice. We investigated the partial correlation between annual decline in test scores and percent change of cGMV. Results: In aMCI patients, changes in the SNSB-D total score (r = 0.340, p < 0.001) and CDR-SOB (r = 0.222, p = 0.020), but not MMSE, showed a correlation with cGMV loss, with the SNSB-D total score showing the strongest correlation. In AD patients, decline in all three test scores correlated significantly with cGMV loss, with MMSE exhibiting the strongest correlation (r = 0.464, p < 0.001). Conclusion: In aMCI patients, neuropsychological battery, though time-consuming, was the most adequate tool in tracking disease progression. In AD patients, however, MMSE may be the most effective longitudinal monitoring tool when considering cost-effectiveness.

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ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients

Cited by 753 publications

References 20 publications

Development of an Objective Autism Risk Index Using Remote Eye Tracking

Development of an Objective Autism Risk Index Using Remote Eye Tracking

Brainstem White Matter Predicts Individual Differences in Manual Motor Difficulties and Symptom Severity in Autism

Tracking Cognitive Decline in Amnestic Mild Cognitive Impairment and Early-Stage Alzheimer Dementia: Mini-Mental State Examination versus Neuropsychological Battery

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