MissForest—non-parametric missing value imputation for mixed-type data

Stekhoven, Daniel J.; Bühlmann, Peter

doi:10.1093/bioinformatics/btr597

Cited by 3,934 publications

(3,107 citation statements)

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“…Model 3 was further controlled for the effects of the co-parents' disorder(s). One hundred multiple imputations were performed using the MissForest procedure based on random forests (Stekhoven and Buhlmann, 2012) to adjust for missing data in coparents (24 diagnoses of SUD, mood and anxiety disorders and 111 diagnoses of behavioral disorders). In an additional model, we adjusted for disorder severity according to the GAF score.…”

Section: Discussionmentioning

confidence: 99%

The specificity of the familial aggregation of early-onset bipolar disorder : A controlled 10-year follow-up study of offspring of parents with mood disorders

Preisig

Strippoli

Castelao

et al. 2016

Journal of Affective Disorders

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Background: Two major sources of heterogeneity of mood disorders that have been demonstrated in clinical, family and genetic studies are the mood disorder subtype (i.e. bipolar (BPD) and major depressive disorder (MDD)) and age of onset of mood episodes. Using a prospective high-risk study design, our aims were to test the specificity of the parent-child transmission of BPD and MDD and to establish the risk of psychopathology in offspring in function of the age of onset of the parental disorder. Methods:Clinical information was collected on 208 probands (n=81 with BPD, n=64 with MDD, n=63 medical controls) as well as their 202 spouses and 372 children aged 6-17 years at study entry.Parents and children were directly interviewed every 3 years (mean duration of follow-up = 10.6 years). Parental age of onset was dichotomized at age 21. Results:Offspring of parents with early onset BPD entailed a higher risk of BPD HR=7.9(1.8-34.6) and substance use disorders HR=5.0(1.1-21.9) than those with later onset and controls. Depressive disorders were not significantly increased in offspring regardless of parental mood disorder subtype or age of onset.Limitations: limited sample size, age of onset in probands was obtained retrospectively, age of onset in co-parents was not adequately documented, and a quarter of the children had no direct interview. Conclusions:Our results provide support for the independence of familial aggregation of BPD from MDD and the heterogeneity of BPD based on patterns of onset. Future studies should further investigate correlates of early versus later onset BPD.

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Section: Discussionmentioning

confidence: 99%

The specificity of the familial aggregation of early-onset bipolar disorder : A controlled 10-year follow-up study of offspring of parents with mood disorders

Preisig

Strippoli

Castelao

et al. 2016

Journal of Affective Disorders

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“…We note that 41 of these accessions are also present in the set of genotypes that we analysed in our study (Supplementary Table 7). Scenario I: we removed 29 out of 199 accessions that did not contain data about at least 50 traits; the missing values for the remaining accessions were imputed for all traits by using the most recent robust imputation method suitable for mixed data types (that is, categorical and continuous) based on random forests via the missForest R package 69 ; Scenario II: we removed 29 out of 199 accessions that did not contain data about at least 50 traits; the missing values for the remaining accessions were imputed for all traits by using random forests imputation method; finally, only defence traits and developmental traits were used; Scenario III: like Scenario II but only for the 41 accession in the overlap between our set of genotypes and the population used in Atwell et al 53 ; Scenario IV: we removed 29 out of 199 accessions that did not contain data about at least 50 traits;…”

Section: Methodsmentioning

confidence: 99%

“…the missing values for the remaining accessions were imputed for only defence traits and developmental traits by using random forests imputation method via the missForest R package 69 ; and Scenario V: like Scenario IV but only for the 41 accession in the overlap between our set of genotypes and the population used in Atwell et al 53 . These five scenarios were necessary to control and investigate the effects of missing values and the way in which they were imputed.…”

Section: Methodsmentioning

confidence: 99%

Metabolic efficiency underpins performance trade-offs in growth of Arabidopsis thaliana

et al. 2014

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Growth often involves a trade-off between the performance of contending tasks; metabolic plasticity can play an important role. Here we grow 97 Arabidopsis thaliana accessions in three conditions with a differing supply of carbon and nitrogen and identify a trade-off between two tasks required for rosette growth: increasing the physical size and increasing the protein concentration. We employ the Pareto performance frontier concept to rank accessions based on their multitask performance; only a few accessions achieve a good trade-off under all three growth conditions. We determine metabolic efficiency in each accession and condition by using metabolite levels and activities of enzymes involved in growth and protein synthesis. We demonstrate that accessions with high metabolic efficiency lie closer to the performance frontier and show increased metabolic plasticity. We illustrate how public domain data can be used to search for additional contending tasks, which may underlie the sub-optimality in some accessions. L iving organisms perform many different and sometimes contending tasks, leading to trade-offs in which optimal performance of one task comes at the cost of a sub-optimal performance of another task. Trade-offs are influenced by the environment and their resolution depends on metabolic resources and plasticity 1,2 . One important environmental variable affecting plant growth is resource availability 3-6 . We first ask whether there is a trade-off between two tasks during vegetative growth of Arabidopsis thaliana: the maximization of physical size and the maximization of protein concentration. We then apply two methods to rank accessions: the first based solely on the performance of tasks, and the second based on the efficiency with which metabolic resources are deployed to perform tasks. In addition, we investigate whether the trade-off and the ranking of accessions are affected by the availability of carbon (C) and nitrogen (N) and the way in which it shapes the accession-specific metabolic profiles.Plants use light energy to transform CO 2 and inorganic nutrients into a plethora of metabolic precursors that are used to drive growth. As plants are sessile, resource acquisition is constrained by their physical size. In land plants, the majority of a mature cell is occupied by the vacuole, allowing the generation of a much larger physical size per unit protein than is usually obtained by microbes or animals 7 . For simplification, we do not consider the impact of shape and phenology on the relation between physical size and resource acquisition. On the other hand, proteins are required to catalyse the transformation of resources into biomass. In particular, the majority of the protein in a plant leaf is involved in photosynthesis [8][9][10] . We hypothesize that there is a trade-off between physical size and protein concentration. While production of leaves with a higher protein concentration will allow higher rates of photosynthesis and metabolism per unit biomass, it also increases the costs of growth a...

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“…In other words, the outcome variables are not assumed to have any particular distributional form (and nor are the errors), and thus can be normal, nonnormal continuous, ordinal, dichotomous, nominal, or count, among others. RFI is conducted using a seven-step process that is outlined in Stekhoven & Bühlmann (2011) paper.…”

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confidence: 99%

Recursive Partitioning Methods for Data Imputation in the Context of Item Response Theory: A Monte Carlo Simulation

Edwards

Finch

2018

Psicológica Journal

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Missing data is a common problem faced by psychometricians and measurement professionals. To address this issue, there are a number of techniques that have been proposed to handle missing data regarding Item Response Theory. These methods include several types of data imputation methods -corrected item mean substitution imputation, response function imputation, multiple imputation, and the EM algorithm, as well as approaches that do not rely on the imputation of missing values -treating the item as not presented, coding missing responses as incorrect, or as fractionally correct. Of these methods, even though multiple imputation has demonstrated the best performance in prior research, higher MAE was still present. Given this higher model parameter estimation MAE for even the best performing missing data methods, this simulation study's goal was to explore the performance of a set of potentially promising data imputation methods based on recursive partitioning. Results of this study demonstrated that approaches that combine multivariate imputation by chained equations and recursive partitioning algorithms yield data with relatively low estimation MAE for both item difficulty and item discrimination. Implications of these findings are discussed.

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MissForest—non-parametric missing value imputation for mixed-type data

Abstract: stekhoven@stat.math.ethz.ch; buhlmann@stat.math.ethz.ch

Cited by 3,934 publications

References 20 publications

The specificity of the familial aggregation of early-onset bipolar disorder : A controlled 10-year follow-up study of offspring of parents with mood disorders

The specificity of the familial aggregation of early-onset bipolar disorder : A controlled 10-year follow-up study of offspring of parents with mood disorders

Metabolic efficiency underpins performance trade-offs in growth of Arabidopsis thaliana

Recursive Partitioning Methods for Data Imputation in the Context of Item Response Theory: A Monte Carlo Simulation

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