PLS model building: A multivariate approach to personality test data

Henningsson, Mikael; Sundbom, Elisabet; Armelius, Bengt‐Åke; Erdberg, Philip

doi:10.1111/1467-9450.00252

Cited by 59 publications

(48 citation statements)

References 9 publications

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“…5a). [31,[44][45][46][47][48] The PLS scores plot shows distinct regions for high (0.8, 0.4 and 0.2 mg cm À2 ), medium (0.1 mg cm À2 ), and low (0.05 and 0.025 mg cm À2 ) exposure levels (Fig. 5a).…”

Section: à2mentioning

confidence: 99%

1H NMR-based metabolomic observation of a two-phased toxic mode of action in Eisenia fetida after sub-lethal phenanthrene exposure

et al. 2011

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Environmental context. Phenanthrene is a persistent soil contaminant, whose toxic mode of action in earthworms has not been fully examined. We adopt a metabolomics approach, using 1 H nuclear magnetic resonance (NMR) spectroscopy, to measure the response of earthworms to sub-lethal phenanthrene exposure. The results indicate that NMR-based metabolomics may be used to monitor responses to sub-lethal levels of contaminants and to delineate their toxic mode of action. Abstract.1 H NMR-based metabolomics was used to examine the response of the earthworm Eisenia fetida to sublethal phenanthrene exposure. E. fetida were exposed via contact tests to six sub-lethal (below the measured LC 50 of 1.6 mg cm À2) concentrations of phenanthrene (0.8-0.025 mg cm À2 ) for 48 h. Multivariate statistical analysis of the 1 H NMR spectra of earthworm tissue extracts revealed a two-phased mode of action (MOA). At exposures below 1/16th of the LC 50 , the MOA was characterised by a linear correlation between the metabolic response and exposure concentration. At exposures !1/16th of the LC 50 , the metabolic response to phenanthrene appeared to plateau, indicating a distinct change in the MOA. Further data analysis suggested that alanine, lysine, arginine, isoleucine, maltose, ATP and betaine may be potential indicators for sub-lethal phenanthrene exposure. Metabolite variation was also found to be proportional to the exposure concentration suggesting that NMR-based earthworm metabolomics is capable of elucidating concentrationdependent relationships in addition to elucidating the MOA of sub-lethal contaminant-exposure.

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Section: à2mentioning

confidence: 99%

1H NMR-based metabolomic observation of a two-phased toxic mode of action in Eisenia fetida after sub-lethal phenanthrene exposure

et al. 2011

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“…This multivariate method [36,37] represents an important development in clinical psychology, which often contains variables that cannot guarantee independence and/or too many variables in relation to the subjects, implying risks for spurious results (Type I and Type II errors). PLS is a regression extension of PCA, aimed at creating a model for prediction of one data set (Y) from another (X).…”

Section: Pls -Partial Least Squares In Latent Structuresmentioning

confidence: 99%

Trauma-related Symptoms after Violent Crime: The Role of Risk Factors before, during and Eight Months after Victimization

Semb¹,

Henningsson²,

Fransson³

et al. 2009

TOPSYJ

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Abstract:The aim of this study was to explore the prevalence of current suffering and the role of peritraumatic emotions and other risk factors for development of post-traumatic and general symptoms eight months post crime. Questionnaires assessing trauma-specific symptoms (HTQ) and general psychiatric symptoms (SCL-90) was used along with a semistructured interview covering subjective reactions of 41 civilian victims of interpersonal crime. Victims proved to still be suffering, in varying degrees, from post-traumatic symptoms and other psychological distress. Females reported more trauma-specific symptoms and other comorbid conditions than males. Prior trauma, adverse childhood, being female, previous psychiatric history, and unemployment were all associated with more distress. Peritraumatic reactions (especially secondary emotions following cognitive appraisals after the event) predicted the three core PTSD symptoms and comorbid conditions. Apart from the PTSD symptoms, an assessment of background factors, general psychiatric symptoms, peritraumatic emotions and their cognitive associated scripts in the initial post-trauma period could be helpful in identifying victims who are at risk of developing trauma symptoms.

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“…A wellknown method is PLS regression, which produces a set of the original predictor variables, a latent variable that are correlated with each other and predict the outcome variable (Eriksson et al, 2006b). So the correlation of predictor variables which may seem to be bothersome in ordinary regression methods, becomes a useful source of information about groups of variables (Henningsson et al, 2001;Richard and Cramer, 1993). PLS has been used in injury research but not for risk assessment purposes in all cases.…”

Section: Discussionmentioning

confidence: 99%

Compared application of the new OPLS-DA statistical model versus partial least squares regression to manage large numbers of variables in an injury case-control study

Sadeghi‐Bazargani¹,

Bangdiwala²,

Mohammad³

et al. 2011

Sci. Res. Essays

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The use of modern statistical methodology to overcome the known pitfalls of classical regression models in the analysis of large numbers of highly correlated data, has increased considerably in recent years. Statisticians in the field of chemometrics and OMICS research have developed a new method called Orthogonal projections to latent structures (OPLS). In comparison with the regular partial least squares (PLS) regression, OPLS provides a simpler method with the additional advantage that the orthogonal variation can be analyzed separately. Use of the OPLS model has spread to fields other than its origin but it is not yet applied to the field of epidemiology, which is a wide field of research. In public health and clinical research, there are situations in which large numbers of correlated variables need to be modeled. The authors successfully applied OPLS-DA to model large numbers of variables in a casecontrol study and compared it with discriminant analysis done by partial least squares regression. Prior to fitting the models, the dataset was split into two parts: a training set and a prediction set. Models fitted on the training dataset were later tested for validity in the prediction dataset. The OPLS-DA was compared with PLS-DA for model fitness, diagnostics and model interpretability. Both models suited the data but OPLS-DA was preferable. The authors encourage the use of these methods to increase study power and statistical validity in epidemiology and similar settings in which large numbers of correlated variables need to be modeled.

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PLS model building: A multivariate approach to personality test data

Cited by 59 publications

References 9 publications

1H NMR-based metabolomic observation of a two-phased toxic mode of action in Eisenia fetida after sub-lethal phenanthrene exposure

1H NMR-based metabolomic observation of a two-phased toxic mode of action in Eisenia fetida after sub-lethal phenanthrene exposure

Trauma-related Symptoms after Violent Crime: The Role of Risk Factors before, during and Eight Months after Victimization

Compared application of the new OPLS-DA statistical model versus partial least squares regression to manage large numbers of variables in an injury case-control study

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