Interference of sample size on multicollinearity diagnosis in path analysis

Sari, Bruno Giacomini; Lúcio, Alessandro Dal’Col; Olivoto, Tiago; Krysczun, Dionatan Ketzer; Tischler, André Luís; Drebes, Lucas

doi:10.1590/s0100-204x2018000600014

Cited by 15 publications

(9 citation statements)

References 8 publications

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“…However, due to the small number of genotypes in the research, the analysis was considered unnecessary. Path analysis with fewer samples can cause multicollinearity (Olivoto et al 2017;Sari et al 2018), hence, this index application could increase the selection effectiveness of synthetic maize under drought stress. Based on the selection index, productivity does not dominate index variance but is the main character, as a result, the index requires adjustment.…”

Section: Resultsmentioning

confidence: 99%

Drought-adapted maize line based on morphophysiological selection index

et al. 2021

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Abstract. Padjung R, Farid M, Musa Y, Anshori MF, Nur A, Masnenong A. 2021. Drought-adapted maize line based on morphophysiological selection index. Biodiversitas 22: 4028-4035. Synthetic line formation is an effort to increase maize productivity in drought-stressed areas. This process requires systematic selection in determining adaptability levels involving important secondary characters formulated in the selection index. Furthermore, the principal component index had been widely reported, both in normal and stressed conditions. The selection index development on morpho-physiological characters based on multivariate analysis was expected to increase drought stress tolerance and maize lines selection precision. Therefore, the purpose of this research was to form a selection index based on morpho-physiological characters and selecting synthetic lines adaptive under drought stress. This research was designed using a split-plot with 3 replications, where the main plot consisted of normal and stressed irrigation, while the subplot was genotype consisting of 6 lines and 3 check varieties namely Bisma, Lamuru, and Sukamarga. Observations were performed on 18 morphological and 4 physiological characters, and the results showed that the selection index was formed based on multivariate analysis from 9 characters. Through index selection, Syn_2-2 (0.79), Syn_2-15 (0.85) and Syn_2-16 (0.97) were considered as drought stress adaptive lines. Therefore, the 3 lines can be recommended in the synthetic variety release process.

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Section: Resultsmentioning

confidence: 99%

Drought-adapted maize line based on morphophysiological selection index

et al. 2021

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“…Some methods could be used to analysis multicollinearity, for instance, Pearson’s correlation coefficients and diagnostics like variance inflation factors and eigenvalues of the correlation matrix (Sari et al , 2018; Sun et al , 2018; Chen et al , 2018). In order to ensure the overall performance of the algorithm, Pearson coefficients are selected to detect collinear factors.…”

Section: Regression Pattern Model and Rp-minermentioning

confidence: 99%

A regression-based algorithm for frequent itemsets mining

Jia

Wang

2019

DTA

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Purpose Frequent itemset mining (FIM) is a basic topic in data mining. Most FIM methods build itemset database containing all possible itemsets, and use predefined thresholds to determine whether an itemset is frequent. However, the algorithm has some deficiencies. It is more fit for discrete data rather than ordinal/continuous data, which may result in computational redundancy, and some of the results are difficult to be interpreted. The purpose of this paper is to shed light on this gap by proposing a new data mining method. Design/methodology/approach Regression pattern (RP) model will be introduced, in which the regression model and FIM method will be combined to solve the existing problems. Using a survey data of computer technology and software professional qualification examination, the multiple linear regression model is selected to mine associations between items. Findings Some interesting associations mined by the proposed algorithm and the results show that the proposed method can be applied in ordinal/continuous data mining area. The experiment of RP model shows that, compared to FIM, the computational redundancy decreased and the results contain more information. Research limitations/implications The proposed algorithm is designed for ordinal/continuous data and is expected to provide inspiration for data stream mining and unstructured data mining. Practical implications Compared to FIM, which mines associations between discrete items, RP model could mine associations between ordinal/continuous data sets. Importantly, RP model performs well in saving computational resource and mining meaningful associations. Originality/value The proposed algorithms provide a novelty view to define and mine association.

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“…O coeficiente de correlação de Pearson é uma ferramenta bastante utilizada para expressar, por meio de um valor puro, a associação entre duas variáveis quantitativas. Entretanto, essa medida é insuficiente para explicar uma relação de causa e efeito (Blind et al, 2018), uma vez que outras podem estar interferindo nessa relação (Oliveira et al, 2018;Sari et al, 2018), conduzindo o pesquisador a conclusões errôneas pela obtenção de valores superestimados.…”

Section: Introductionunclassified

Relação entre índice de colheita do milho e eficiências de fósforo por meio de análise de trilha

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et al. 2021

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A produtividade das diversas culturas, incluindo o milho, é influenciada pela habilidade das plantas em absorver e utilizar nutrientes. O objetivo foi verificar, por meio da análise de trilha, as relações diretas e indiretas entre o índice de colheita e as eficiências de uso de fósforo no milho. As variáveis do estudo foram: índice de colheita do milho (HI), índice de colheita para fósforo (FO), eficiência de uso compartimentalizado na folha (CF), eficiência de uso compartimentalizado no caule (CC), eficiência de uso compartimentalizado na palha (CP), eficiência de uso compartimentalizado no grão (CG), eficiência de uso integralizado na folha (IF), eficiência de uso integralizado no caule (IC), eficiência de uso integralizado na palha (IP). Por meio da correlação de Pierson, observamos correlação alta e positiva entre CP e IP, CF e IF e IC e FO. Houve correlação forte e negativa entre: IC e IP, IC e CP e FO e CG. O Concluiu-se que as variáveis que obtiveram os maiores efeitos diretos e positivos sobre o índice de colheita do milho foram: índice de colheita para fosforo e eficiência de uso compartimentalizado no grão. Efeitos diretos e negativos sobre o índice de colheita do milho foram: eficiência de uso compartimentalizado na palha e eficiência de uso compartimentalizado na folha. De forma indireta, a análise de trilha mostrou que eficiência de uso compartimentalizado no grão e eficiência de uso integralizado na folha são fortemente correlacionados positivamente, e no sentido oposto, eficiência de uso compartimentalizado no grão e índice de colheita para fósforo são correlacionados negativamente.

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Interference of sample size on multicollinearity diagnosis in path analysis

Cited by 15 publications

References 8 publications

Drought-adapted maize line based on morphophysiological selection index

Drought-adapted maize line based on morphophysiological selection index

A regression-based algorithm for frequent itemsets mining

Relação entre índice de colheita do milho e eficiências de fósforo por meio de análise de trilha

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