rFSA: An R Package for Finding Best Subsets and Interactions

Lambert, Joshua; Gong, Liyu; Elliott, Corrine F.; Thompson, Katherine; Stromberg, Arnold J.

doi:10.32614/rj-2018-059

Cited by 28 publications

(19 citation statements)

References 11 publications

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“…Next, an advanced variable selection process was used, through addition and removal, back and forth, in the logistic regression model to determine the best candidates for predicting the driver fault status. Potential interactions were tested using an interactive web-based tool called the feasible solution algorithm (FSA) to improve the strength and stability of the model ( 14 , 28 ). FSA helps explore large subsets or higher-order interaction terms in statistical modeling that utilized big databases aiming to identify possible variable interactions.…”

Section: Methodsmentioning

confidence: 99%

Effect of Socioeconomic and Demographic Factors on Crash Occurrence

Sagar¹,

Stamatiadis

Stromberg

2021

Transportation Research Record: Journal of the Transportation R

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The number of crashes and fatalities rate in the Commonwealth of Kentucky, U.S., have been higher than the national average for the past decades. It has been hypothesized that the distinct socioeconomic conditions of the state could be contributing to and explaining these trends. This study investigated the influence of socioeconomic characteristics on highway safety in Kentucky and attempted to identify the high-risk driver groups, based on crash data and the socioeconomic and demographic features of their residence zip codes. The quasi-induced exposure technique and binary logistic regression were employed to develop a predictive modeling approach for determining the probability of being the at-fault driver in a single- and two-unit crashes, based on socioeconomic characteristics of the driver residence zip code. The study identified that socioeconomic features such as income, poverty level, employment, age, gender, rurality, and number of traffic-related convictions of a driver’s zip code influence their likelihood to be at fault in a two-unit crash, while for single-unit crashes, in addition to these variables, educational attainment had also an impact. Younger and older drivers living in zip codes with low socioeconomic conditions have a higher probability to be the at-fault driver in both single- and two-unit crashes. The conclusions of the study can be used to determine the regions (zip codes) and driver groups with higher likelihood to be the at-fault driver in a crash and develop effective safety programs for the target groups.

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Section: Methodsmentioning

confidence: 99%

Effect of Socioeconomic and Demographic Factors on Crash Occurrence

Sagar¹,

Stamatiadis

Stromberg

2021

Transportation Research Record: Journal of the Transportation R

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“…As shown by Gupta [ 87 ], Hosmer et al [ 88 ], and Sullivan and Wilson [ 89 ], this can be done by applying the stepwise regression technique. Among the stepwise regression variations, the best subsets approach (BSA) has gained particularly widespread acceptance in contemporary studies on multicollinearity [ 10 , 90 , 91 ] and prediction of interactions between variables in large arrays [ 92 , 93 , 94 ].…”

Section: Methodsmentioning

confidence: 99%

The Supply of Calories, Proteins, and Fats in Low-Income Countries: A Four-Decade Retrospective Study

Erokhin

Tianming

et al. 2021

IJERPH

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Over the past decades, both the quantity and quality of food supply for millions of people have improved substantially in the course of economic growth across the developing world. However, the number of undernourished people has resumed growth in the 2010s amid food supply disruptions, economic slowdowns, and protectionist restrictions to agricultural trade. Having been common to most nations, these challenges to the food security status of the population still vary depending on the level of economic development and national income of individual countries. In order to explore the long-run determinants of food supply transformations, this study employs five-stage multiple regression analysis to identify the strengths and directions of effects of agricultural production parameters, income level, price indices, food trade, and currency exchange on supply of calories, proteins, and fats across 11 groups of agricultural products in 1980–2018. To address the diversity of effects across developing nations, the study includes 99 countries of Asia, Europe, Latin America, the Middle East, and Africa categorized as low-income, lower-middle-income, and upper-middle-income economies. It is found that in low-income countries, food supply parameters are more strongly affected by production factors compared to economic and trade variables. The effect of economic factors on the food supply of higher-value food products, such as meat and dairy products, fruit, and vegetables, increases with the rise in the level of income, but it stays marginal for staples in all three groups of countries. The influence of trade factors on food supply is stronger compared to production and economic parameters in import-dependent economies irrelevant of the gross national income per capita. The approach presented in this paper contributes to the research on how food supply patterns and their determinants evolve in the course of economic transformations in low-income countries.

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“…We enumerated the possible solutions with interacting miRNA (n = 23), regardless of direction of expression relative to the mRNA (http://CRAN.R-project.org/package=rFSA). 21…”

Section: Methodsmentioning

confidence: 99%

“…org/package=rFSA). 21 We examined the 100 probeIDs with the highest potential of representing a solution (Supplementary Table 1) for further biological evaluation by overlaying onto a molecular interaction network provided by STRING. 22 Using the miRNA-mRNA interactions found by the FSA, the Affymetrix probeIDs were converted to Ensembl IDs.…”

Section: The Fsa Statistical Methodology and Interaction Network Analmentioning

confidence: 99%

Deregulation of a Network of mRNA and miRNA Genes Reveals That CK2 and MEK Inhibitors May Synergize to Induce Apoptosis KRAS-Active NSCLC

et al. 2019

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KRAS-activation mutations occur in 25% to 40% of lung adenocarcinomas and are a known mechanism of epidermal growth factor receptor inhibitor (EGFRI) resistance. There are currently no targeted therapies approved specifically for the treatment of KRAS-active non–small cell lung cancers (NSCLC). Attempts to target mutant KRAS have failed in clinical studies leaving no targeted therapy option for these patients. To circumvent targeting KRAS directly, we hypothesized that targeting proteins connected to KRAS function rather than targeting KRAS directly could induce cell death in KRAS-active NSCLC cells. To identify potential targets, we leveraged 2 gene expression data sets derived from NSCLC cell lines either resistant and sensitive to EGFRI treatment. Using a Feasible Solutions Algorithm, we identified genes with deregulated expression in KRAS-active cell lines and used STRING as a source for known protein-protein interactions. This process generated a network of 385 deregulated proteins including KRAS and other known mechanisms of EGFRI resistance. To identify candidate drug targets from the network for further study, we selected proteins with the greatest number of connections within the network and possessed an enzymatic activity that could be inhibited with an existing pharmacological agent. Of the potential candidates, the pharmacological impact of targeting casein kinase 2 (CK2) as a single target was tested, and we found a modest reduction in viability in KRAS-active NSCLC cells. MEK was chosen as a second target from outside the network because it lies downstream of KRAS and MEK inhibition can overcome resistance to CK2 inhibitors. We found that CK2 and MEK inhibition demonstrates moderate synergy in inducing apoptosis in KRAS-active NSCLC cells. These results suggest promise for a combination inhibitor strategy for treating KRAS-active NSCLC.

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rFSA: An R Package for Finding Best Subsets and Interactions

Cited by 28 publications

References 11 publications

Effect of Socioeconomic and Demographic Factors on Crash Occurrence

Effect of Socioeconomic and Demographic Factors on Crash Occurrence

The Supply of Calories, Proteins, and Fats in Low-Income Countries: A Four-Decade Retrospective Study

Deregulation of a Network of mRNA and miRNA Genes Reveals That CK2 and MEK Inhibitors May Synergize to Induce Apoptosis KRAS-Active NSCLC

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