Partial least squares regression in the social sciences

Sawatsky, Megan L.; Clyde, Matthew; Meek, Fiona

doi:10.20982/tqmp.11.2.p052

Cited by 59 publications

(37 citation statements)

References 16 publications

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“…PLSR differs from PCA in that the latter creates components that focus on the variation observed in the independent variables without considering the dependent variable, whereas PLSR also considers the variability in the dependent variable to maximize the covariance between them (WOLD et al, 2001). PLSR is a widely used technique in natural sciences, but it is rarely used in social sciences (SAWATSKY et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

“…San Pedro and Oliveira (2013) performed a systematic literature review on the relation between socioeconomic factors (individual and collective) and occurrence of pulmonary TB. Regarding the collective studies, the authors identified the important influence of variables related to the gross national product (GNP) per capita, human development index, and level of access to basic sanitation in the country scale.…”

Section: Introductionmentioning

confidence: 99%

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Spatial Distribution of Pulmonary Tuberculosis in Urban Areas: A Case From Belém, Brazil

2016

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The precise location of areas with high incidence of pulmonary tuberculosis (TB) is important to improve public health actions. Official data records of the addresses and neighborhoods where the infected people live allow the mapping of the disease on this spatial scale. However, great socioeconomic diversity often exists inside neighborhoods, wherein highand low-income families reside. This situation hampers the location of those areas that require close attention. Objective: This study aimed to estimate the risk of pulmonary TB infections in census tracts in Belém City (Brazil) from data on neighborhoods. Methods: A partial leastsquares regression model was constructed in the scale of neighborhoods based on the record of addresses of TB-infected people and socioeconomic data from official sources. The model was then slightly modified and used to estimate the risk of TB prevalence in urban census tracts. The results were mapped using a geographical information system. Results: The percentages of explained variance of the set of independent variables and dependent variable were 86.4% and 30.2%, respectively. These values indicated that the model is acceptable for its purpose. Conclusion: The model's results were consistent with the spatial distribution of socioeconomic and environmental characteristics of Belém City.Keywords: Tuberculosis Pulmonary; Urban Population; Public Health. RESUMOA localização precisa das áreas com alta incidência de tuberculose pulmonar (TB) é importante para melhorar as ações de saúde pública. Os dados oficiais registram endereços e bairros onde moram pessoas infectadas, permitindo o mapeamento da enfermidade nesta escala espacial. Comumente, porém, há grande diversidade socioeconômica no interior dos bairros, onde coexistem áreas com famílias de alta e baixa renda. Isso dificulta a localização das áreas prioritárias para ação. Objetivo: estimar o risco de infecções por tuberculose pulmonar (TB) nos setores censitários na cidade de Belém (PA), a partir de dados por bairros. Métodos: construção de um modelo de regressão múltipla de mínimos quadrados parciais, na escala dos bairros, com base no cadastro de endereços de pessoas infectadas e dados socioeconômicos de fontes oficiais. O modelo, com uma pequena modificação, foi então usado para estimar o risco de incidência de TB nos setores censitários urbanos. Em seguida, os resultados foram mapeados por meio de um sistema de informações geográficas. Resultados: o percentual de variância explicada do conjunto de variáveis independentes foi de 86,4% e o da variável dependente, 30,2%; valores que tornam o modelo aceitável para o fim proposto. Conclusão: o modelo mostrou resultados coerentes com a distribuição espacial das características socioeconômicas e ambientais da cidade de Belém.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial Distribution of Pulmonary Tuberculosis in Urban Areas: A Case From Belém, Brazil

2016

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“…Prior to PLS analysis, data were log10 transformed, centered, and scaled (Sawatsky et al, 2015). Seed for all four varieties was derived from the same company and together, was grown on more than half (177 fields) of all sampled fields (data not shown).…”

Section: Discussionmentioning

confidence: 99%

“…Seed for all four varieties was derived from the same company and together, was grown on more than half (177 fields) of all sampled fields (data not shown). van der Voet's test and the minimum predicted residual sum of squares (PRESS) was used to test the integrity of the pruned models (Sawatsky et al, 2015;Wold, 1975). Prior to PLS analysis, data were log10 transformed, centered, and scaled (Sawatsky et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the Causes of On‐Farm Harvest Losses in Canola in the Northern Great Plains

et al. 2016

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Canola (Brassica napus L.) is the main oilseed crop grown in the northern Great Plains (Canada). This species, however, also is associated with significant seed losses before and during harvest. To determine the factors that contribute to on‐farm harvest losses in B. napus, an extensive on‐farm survey was conducted in four regions across the northern Great Plains in 2010, 2011, and 2012. In addition to measuring on‐farm harvest losses on 310 fields, a survey questionnaire was used to collect agronomic data for each field and wind data from the nearest local weather station was used to determine wind speed during the harvest season. This study showed that total on‐farm harvest losses in canola are a complex phenomenon. This study identified that managing harvest losses in B. napus begins at the time of planting. Management factors that contributed to increased yield were linked to lower proportional B. napus harvest losses. Other factors that contributed to reduced proportional harvest losses included a fungicide application at flowering, earlier windrowing and harvest dates, lower combine harvester ground speed, and reduced windrower width. Factors considered by producers as important, such as combine manufacturer or B. napus variety did not contribute significantly to total harvest losses in this crop. Nevertheless, clear management practices were identified that can be employed to minimize on‐farm harvest losses in B. napus. A better understanding of the contributions of environmental variables to harvest losses in this species is required, particularly as interest in direct‐harvesting B. napus continues to increase in western Canada.

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“…The test result shows that weigth value almost all indicator variables produce significant weight value, that is not less than 0,1, that is allowed limit value [29]. Only one indicator variable whose value is less than 0.1 is a gender variable with a value of 0.048, so the gender variable can be excluded from the model.…”

Section: A Establishing the Structure For The Relationship Between Fmentioning

confidence: 97%

Improved-Node-Probability Method for Decision Making in Priority Determination of Village Development Proposed Program

Trisnawarman¹,

Hartati²,

Winarko³

et al. 2017

ijacsa

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Abstract-This research proposes a new method, the probability of nodes (NP) and the cumulative frequency of indicators within the framework of Bayesian networks to calculate the weight of participation. This method uses the PLS-PM approach to examine the relationship structure of participatory factors and estimate latent variables. Data were collected using questionnaires involving participants offering proposals, the village residents themselves. The participation factors identified in this research were divided into two categories, namely, internal factors (abilities) and external factors (motivation). The internal factors included gender, age, education, occupation, and income, while the external factors included motivation relating to economic, political, sociocultural, norm-related, and knowledge-related issues. Moreover, there are three factors directly affecting the level of participation, they are: the level of attendance in meetings, participation in giving suggestions, and involvement in decision making. The test results showed that the application of participation weight in decision making priority of proposal of village development program give change of final rank of decision with test result as: recall 50%, precision 80% and accuracy 50%.

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Partial least squares regression in the social sciences

Cited by 59 publications

References 16 publications

Spatial Distribution of Pulmonary Tuberculosis in Urban Areas: A Case From Belém, Brazil

Spatial Distribution of Pulmonary Tuberculosis in Urban Areas: A Case From Belém, Brazil

Evaluation of the Causes of On‐Farm Harvest Losses in Canola in the Northern Great Plains

Improved-Node-Probability Method for Decision Making in Priority Determination of Village Development Proposed Program

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