Comparison of Stopping Rules in Forward "Stepwise" Regression

1977 ◽  
Vol 72 (357) ◽  
pp. 46 ◽  
Author(s):  
Robert B. Bendel ◽  
A. A. Afifi
Keyword(s):  
Stepwise Regression ◽  
Stopping Rules ◽  
Forward Stepwise

A comparison of sample preparation and calibration techniques for the estimation of nitrogen, oil and glucosinolate content of rapeseed by near infrared spectroscopy

1985 ◽  
Vol 104 (2) ◽  
pp. 317-323 ◽  
Author(s):  
Carol Starr ◽  
Janet Suttle ◽  
A. G. Morgan ◽  
D. B. Smith
Keyword(s):  
Stepwise Regression ◽  
Near Infrared ◽  
Glucosinolate Content ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Reflectance Analysis ◽  
Glucosinolate Concentration ◽  
Forward Stepwise ◽  
Calibration Techniques ◽  
Reflectance Data

SummaryPredictions of nitrogen, oil and glucosinolate concentration in rapeseed samples were made by near infrared reflectance analysis after various grinding treatments. Also examined were the effects of normalizing reflectance data and the possible advantage of using all combinations of two and three wavelengths in the calibration regression analysis over forward stepwise regression. The main conclusion was that drying the samples prior to a controlled grinding treatment gave the best results, although acceptable results for selection purposes could be obtained using whole seeds to predict nitrogen and oil. None of the treatments of the seed or reflectance data allowed acceptable prediction of glucosinolate content.

Predictors for compliance with anti-terrorist financing standards

2019 ◽  
Vol 22 (2) ◽  
pp. 257-269
Author(s):  
Erik Joosten ◽  
Marion Bogers ◽  
Robert Beeres ◽  
Robert Bertrand
Keyword(s):  
Financial Market ◽  
Stepwise Regression ◽  
Common Belief ◽  
Content Type ◽  
Terrorist Financing ◽  
Tourism Sector ◽  
Forward Stepwise ◽  
Financial Action Task ◽  
Practical Implications ◽  
Additional Variance

Purpose The purpose of this paper is to identify and test predictors for countries to comply with the Financial Action Task Force’s (FATF) anti-money laundering and terrorist financing recommendations. Design/methodology/approach The authors conduct a quantitative study to explore which factors predict compliance of countries. They include the compliance scores of 196 countries. Findings The results of a forward stepwise regression analysis show that a country’s wealth, measured as gross domestic product (GDP) per capita, is the most important predictor for compliance. This result supports earlier academic work about predictors for compliance (Simmons, 1998; Giraldo and Trinkunas, 2007; Whitaker, 2010). The other factors identified suffering from terrorist attacks, relative financial market dominance, tourism sector and the degree of democracy do not explain additional variance in compliance. Practical implications This research sheds light on compliance as a concept. For policymakers, accountants, companies and governments, it is important to understand why compliance occurs and why not. Originality/value The empirical results indicate that, in contrast to common belief, countries that suffer more from terrorism are not more compliant. Moreover, the rate of democracy, a relative dominant financial market and a strong tourism sector do not stimulate compliance with anti-terrorist financing standards.

An Interpersonal Analysis of Rorschach Aggression Variables in a Normal Sample

2001 ◽  
Vol 89 (3) ◽  
pp. 617-623 ◽  
Author(s):  
Joni L. Mihura ◽  
Elizabeth Nathan-Montano
Keyword(s):  
Stepwise Regression ◽  
The Self ◽  
The Other ◽  
Self Report ◽  
Normal Sample ◽  
Regression Analyses ◽  
Forward Stepwise ◽  
Interpersonal Control ◽  
The Relationship ◽  
Report Measure

This study investigated the relationship between Rorschach aggression variables and a self-report measure of interpersonal control and aggression (Structural Analysis of Social Behavior), rated for best and worst states, with 50 college students using forward stepwise regression analyses Aggressive Movement (AG) was related to the report of self-attack for the best state ratings The following findings were significant for the worst state ratings. AG was related to viewing the other as reacting as if attacked but the self as acting more affiliatively to the other. Aggressive Past (AgPast) was related to reacting to the other more submissively. A combined Aggressive Potential (AgPot)/Aggressive Content (AgC) variable was related to viewing the other as reacting less submissively and acting more dominantly. AgC was related to viewing the other as reacting less submissively. Methodological limitations are discussed, including potential problems regarding social desirability for the self-report aggression measure.

Forward-stepwise regression analysis for fine leak batch testing of wafer-level hermetic MEMS packages

2010 ◽  
Vol 50 (4) ◽  
pp. 507-513 ◽  
Author(s):  
Changsoo Jang ◽  
Byeng Dong Youn ◽  
Ping F. Wang ◽  
Bongtae Han ◽  
Suk-Jin Ham
Keyword(s):  
Regression Analysis ◽  
Stepwise Regression ◽  
Stepwise Regression Analysis ◽  
Wafer Level ◽  
Batch Testing ◽  
Forward Stepwise

scholarly journals Centennial-scale variability of terrestrial near-surface wind speed over China from reanalysis

2021 ◽  
pp. 1-52
Author(s):  
Cheng Shen ◽  
Jinlin Zha ◽  
Jian Wu ◽  
Deming Zhao
Keyword(s):  
Wind Speed ◽  
Large Scale ◽  
Stepwise Regression ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Wind Speeds ◽  
Ocean Atmosphere ◽  
Forward Stepwise ◽  
Strong Winds

AbstractInvestigations of variations and causes of near-surface wind speed (NWS) further understanding of the atmospheric changes and improve the ability of climate analysis and projections. NWS varies on multiple temporal scales; however, the centennial-scale variability in NWS and associated causes over China remains unknown. In this study, we employ the European Centre for Medium-Range Weather Forecasts (ECMWF) twentieth century reanalysis (ERA-20C) to study the centennial-scale changes in NWS from 1900–2010. Meanwhile, a forward stepwise regression algorithm is used to reveal the relationships between NWS and large-scale ocean-atmosphere circulations. The results show three unique periods in annual mean NWS over China from 1900–2010. The annual mean NWS displayed a decreasing trend of -0.87% decade-1 and -11.75% decade-1 from 1900–1925 and 1957–2010, respectively, which were caused by the decreases in the days with strong winds, with trends of -6.64 and -4.66 days decade-1, respectively. The annual mean NWS showed an upward trend of 55.47% decade-1 from 1926–1956, which was caused by increases in the days with moderate (0.43 days decade-1) and strong winds (23.55 days decade-1). The reconstructed wind speeds based on forward stepwise regression algorithm matched well with the original wind speeds; therefore, the decadal changes in NWS over China at centennial-scale were mainly induced by large-scale ocean-atmosphere circulations, with the total explanation power of 66%. The strongest explanation power was found in winter (74%), and the weakest explanation power was found in summer (46%).

Personality Characteristics of Volunteers in a Companion for Children Program

1986 ◽  
Vol 59 (2) ◽  
pp. 819-825 ◽  
Author(s):  
Donald M. Burke ◽  
Maureen Hall
Keyword(s):  
Stepwise Regression ◽  
Personality Characteristics ◽  
Personal Factors ◽  
The Social ◽  
Forward Stepwise ◽  
Social Introversion ◽  
Screening Device

This study evaluated the effectiveness of the MMPI and other personal factors in predicting both the length of time the volunteer would be in the program and the quality of performance of the volunteer in a Companions for Children program. The MMPI scores of 67 volunteers, over a 2-yr. period, were evaluated. There were some significant correlations between longevity in program, specifically occupation, education, and scores on the Hysteria scale of the MMPI were negatively correlated. The staff-rated quality of the volunteers, education, and occupation were significantly correlated, as well as scores on the Psychasthenia scale of the MMPI. A forward stepwise regression, performed for longevity and rated quality, showed education, scores on the F scale, Hysteria scale, and Psychasthenia scale were the four best indicators of longevity. The best four indicators for rated quality were the F scale, Hypochondriasis scale, Schizophrenia scale, and the Social introversion-extroversion scale. Although the MMPI was a good screening device, it was not an adequate predictor of eventual longevity or quality in the program.

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