Multiple Linear Regression Model for Improved Project Cost Forecasting

Ottaviani, Filippo Maria; Marco, Alberto De

doi:10.1016/j.procs.2021.12.079

Cited by 30 publications

(10 citation statements)

References 20 publications

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“…Another possible scenario is when the researcher aims to determine which predictors (or variables) should be regarded as not important or less important. In some cases, proving that a variable does not correlate with another variable can also be considered an important finding [ 15 16 ].…”

Section: Discussionmentioning

confidence: 99%

An elaboration on sample size determination for correlations based on effect sizes and confidence interval width: a guide for researchers

Bujang

2024

Restor Dent Endod

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Objectives This paper aims to serve as a useful guide for sample size determination for various correlation analyses that are based on effect sizes and confidence interval width. Materials and Methods Sample size determinations are calculated for Pearson’s correlation, Spearman’s rank correlation, and Kendall’s Tau-b correlation. Examples of sample size statements and their justification are also included. Results Using the same effect sizes, there are differences between the sample size determination of the 3 statistical tests. Based on an empirical calculation, a minimum sample size of 149 is usually adequate for performing both parametric and non-parametric correlation analysis to determine at least a moderate to an excellent degree of correlation with acceptable confidence interval width. Conclusions Determining data assumption(s) is one of the challenges to offering a valid technique to estimate the required sample size for correlation analyses. Sample size tables are provided and these will help researchers to estimate a minimum sample size requirement based on correlation analyses.

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Section: Discussionmentioning

confidence: 99%

An elaboration on sample size determination for correlations based on effect sizes and confidence interval width: a guide for researchers

Bujang

2024

Restor Dent Endod

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“…PPPs awarded before the COVID-19 pandemic and the ones that will be procured in the postpandemic could face the risk of early termination because of the effects derived from the aftermath of the crisis. These PPPs could avoid early terminations by improving project cost forecasting [35]. Alternatively, it is possible reducing the costs of ongoing PPPs by changing the project's scope or achieving cost reductions in the shaping phase accordingly.…”

Section: Clusters' Discussionmentioning

confidence: 99%

Crisis Driven Literature in PPPs: A Network Analysis

Castelblanco

Guevara

2022

IOP Conf. Ser.: Earth Environ. Sci.

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COVID-19 crisis has simultaneously triggered a global economic crisis whose consequences will lead to a dichotomy where several governments’ debt has grown to unprecedented levels and simultaneously is required to promote new infrastructure supply. This global economic crisis scenario endangers current Public-Private Partnership (PPP) programs given their dependence on payment from the user and/or government subsidies in long-term lifecycles. This study aims for unravelling the PPP research agenda derived from the last global economic crisis in 2008 and the current one for understanding the trends developed as a tool for building a post-pandemic PPP research agenda. For understanding the last global financial crisis PPP literature review and its time and geographic evolution since 2008, this study developed a literature review employing Network Analysis. Therefore, crisis- and PPP-related keywords were combined for establishing the search in the Web of Science database. After removing duplicate papers, 67 peer-reviewed articles were identified for recognizing underpinning topics, potential gaps, and time evolution. The network analysis revealed seven clusters driven by payment sources (i.e., public financial aspects, user payments, and demand), contract mechanisms (i.e., contractual governance, and risk valuation), and project performance (i.e., project performance under crisis and project efficiency). This paper contributes to the PPP body of knowledge by unraveling the post-global economic crisis agenda and its gaps in proposing a new research agenda for overcoming the consequences of the global economic crisis derived from the COVD-19 pandemic.

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“…MRL provides mathematical calculations on the parameters and outputs used in conducting the analysis [48]. The MRL results can prove the results of the analysis based on the correlation test in each indicator variable [49]. Overall MRL can see the relationship pattern data significantly [50].…”

Section: Multiple Linear Regression (Mrl)mentioning

confidence: 90%

Machine learning classification analysis model community satisfaction with traditional market facilities as public service

Syahputra

Yanto

Putra

et al. 2023

IJ-AI

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Traditional markets are public service facilities that can be utilized by the community. The market function is used place where sellers and buyers meet in conducting transactions. This study aims to build a machine learning classification analysis model in measuring community satisfaction with traditional market facilities. The analytical methods used include Fuzzy. multiple linear regression (MRL), artificial neural network (ANN), and decision tree (DT). Fuzzy is used to generate a pattern of rules in determining the level of satisfaction. MRL serves to measure and test the correlation of rules that have been formed. The ANN method is used to carry out the classification analysis process based on learning. In the final stage. DT is used to describe the decision tree of the analysis process. This study presents the results of machine learning analysis which is very good in determining satisfaction with an accuracy rate of 99.99%. This result is influenced by fuzzy logic which can develop a classification rule pattern of 32 patterns. MRL also shows a significant correlation level of 81.1% based on the indicator variables. Overall, the machine learning classification analysis model can provide knowledge to be considered in the management of traditional markets as public service facilities.

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Multiple Linear Regression Model for Improved Project Cost Forecasting

Cited by 30 publications

References 20 publications

An elaboration on sample size determination for correlations based on effect sizes and confidence interval width: a guide for researchers

An elaboration on sample size determination for correlations based on effect sizes and confidence interval width: a guide for researchers

Crisis Driven Literature in PPPs: A Network Analysis

Machine learning classification analysis model community satisfaction with traditional market facilities as public service

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