Appendix 2: Definition, measurement, calculation, and data sources of the variables used in the regression analysis

Price of tobacco products has traditionally been relevant both for the industry, to respond to policy changes, and for governments, as an effective tobacco control measure. However, monitoring prices across a wide range of brands and brand variants requires access to expensive commercial sales databases. This study aims to investigate the comparability of average tobacco prices from two commercial sources and an in-house monitoring database which provides daily data in real time at minimal cost. We used descriptive and regression analysis to compare the monthly average numbers of brands, brand variants, products and prices of cigarettes and hand-rolling tobacco using commercial data from Nielsen Scantrack and Kantar Worldpanel, and an online price database (OPD) created in Nottingham, for the period from May 2013 to February 2017. There were marked differences in the number of products tracked in the three data sources. Nielsen was the most comprehensive and Kantar Worldpanel the least. Though average prices were very similar between the three datasets, Nottingham OPD prices were the highest and Kantar Worldpanel the lowest. However, regression analysis demonstrated that after adjustment for differences in product range, price differences between the datasets were very small. After allowing for differences in product range these data sources offer representative prices for application in price research. Online price tracking offers an inexpensive and near real-time alternative to the commercial datasets.

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Pengaruh Partisipasi Anggaran, Informasi Asimetris Dan Budget Emphasis Terhadap Slack Anggaran

JURNAL PUNDI ◽

10.31575/jp.v2i3.106 ◽

2018 ◽

Vol 2 (3) ◽

Author(s):

Elsa Meirina

Keyword(s):

Regression Analysis ◽

Asymmetric Information ◽

Performance Measurement ◽

Multiple Regression Analysis ◽

Multiple Regression ◽

Data Sources ◽

Allocation Of Resources ◽

Budgetary Slack ◽

West Sumatra ◽

Budgetary Participation

Budget slack is a behavior of individuals and organizations in preparing budgets even more so if the budget is used as a basis for performance measurement. The occurrence of a budget slack, namely budgetary slack will make the performance look better in the eyes of superiors if they can achieve the budget goals. Budgetary slacks are often used to overcome uncertainties predicting the future and the allocation of resources will be carried out based on the projected budget costs, so that slack makes flexible. Budgetary participation, asymmetric information, and budget emphasis are factors that influence the occurrence of budget slack. The study was conducted at the Badan Perencanaan dan Pembangunan Daerah (BAPPEDA) of West Sumatra with a total of 50 respondents consisting of heads of departments, heads of fields, sub-sections, and other employees related to the budget. Data sources in this study are questionnaires that use multiple regression analysis. The results of the research that have been conducted show that asymmetric information affects the occurrence of budget slack. Information owned by subordinates or superiors is the basis for setting the markup level on the budget.

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Automatable Distributed Regression Analysis of Vertically Partitioned Data Facilitated by PopMedNet: Feasibility and Enhancement Study (Preprint)

10.2196/preprints.21459 ◽

2020 ◽

Author(s):

Qoua Her ◽

Thomas Kent ◽

Yuji Samizo ◽

Aleksandra Slavkovic ◽

Yury Vilk ◽

...

Keyword(s):

Regression Analysis ◽

Real World ◽

Data Sources ◽

Patient Privacy ◽

File Transfer ◽

Level Information ◽

Partitioned Data ◽

Analysis Center ◽

Vertically Partitioned Data ◽

Technical Capability

BACKGROUND In clinical research, important variables may be collected from multiple data sources. Physical pooling of patient-level data from multiple sources often raises several challenges, including proper protection of patient privacy and proprietary interests. We previously developed an SAS-based package to perform distributed regression—a suite of privacy-protecting methods that perform multivariable-adjusted regression analysis using only summary-level information—with horizontally partitioned data, a setting where distinct cohorts of patients are available from different data sources. We integrated the package with PopMedNet, an open-source file transfer software, to facilitate secure file transfer between the analysis center and the data-contributing sites. The feasibility of using PopMedNet to facilitate distributed regression analysis (DRA) with vertically partitioned data, a setting where the data attributes from a cohort of patients are available from different data sources, was unknown. OBJECTIVE The objective of the study was to describe the feasibility of using PopMedNet and enhancements to PopMedNet to facilitate automatable vertical DRA (vDRA) in real-world settings. METHODS We gathered the statistical and informatic requirements of using PopMedNet to facilitate automatable vDRA. We enhanced PopMedNet based on these requirements to improve its technical capability to support vDRA. RESULTS PopMedNet can enable automatable vDRA. We identified and implemented two enhancements to PopMedNet that improved its technical capability to perform automatable vDRA in real-world settings. The first was the ability to simultaneously upload and download multiple files, and the second was the ability to directly transfer summary-level information between the data-contributing sites without a third-party analysis center. CONCLUSIONS PopMedNet can be used to facilitate automatable vDRA to protect patient privacy and support clinical research in real-world settings.

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Automatable Distributed Regression Analysis of Vertically Partitioned Data Facilitated by PopMedNet: Feasibility and Enhancement Study

JMIR Medical Informatics ◽

10.2196/21459 ◽

2021 ◽

Vol 9 (4) ◽

pp. e21459

Author(s):

Qoua Her ◽

Thomas Kent ◽

Yuji Samizo ◽

Aleksandra Slavkovic ◽

Yury Vilk ◽

...

Keyword(s):

Regression Analysis ◽

Real World ◽

Data Sources ◽

Patient Privacy ◽

File Transfer ◽

Level Information ◽

Partitioned Data ◽

Analysis Center ◽

Vertically Partitioned Data ◽

Technical Capability

Background In clinical research, important variables may be collected from multiple data sources. Physical pooling of patient-level data from multiple sources often raises several challenges, including proper protection of patient privacy and proprietary interests. We previously developed an SAS-based package to perform distributed regression—a suite of privacy-protecting methods that perform multivariable-adjusted regression analysis using only summary-level information—with horizontally partitioned data, a setting where distinct cohorts of patients are available from different data sources. We integrated the package with PopMedNet, an open-source file transfer software, to facilitate secure file transfer between the analysis center and the data-contributing sites. The feasibility of using PopMedNet to facilitate distributed regression analysis (DRA) with vertically partitioned data, a setting where the data attributes from a cohort of patients are available from different data sources, was unknown. Objective The objective of the study was to describe the feasibility of using PopMedNet and enhancements to PopMedNet to facilitate automatable vertical DRA (vDRA) in real-world settings. Methods We gathered the statistical and informatic requirements of using PopMedNet to facilitate automatable vDRA. We enhanced PopMedNet based on these requirements to improve its technical capability to support vDRA. Results PopMedNet can enable automatable vDRA. We identified and implemented two enhancements to PopMedNet that improved its technical capability to perform automatable vDRA in real-world settings. The first was the ability to simultaneously upload and download multiple files, and the second was the ability to directly transfer summary-level information between the data-contributing sites without a third-party analysis center. Conclusions PopMedNet can be used to facilitate automatable vDRA to protect patient privacy and support clinical research in real-world settings.

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Appendix D: Data Sources for Regression Analysis (Chapter 3)

10.7560/738379-015 ◽

1986 ◽

pp. 219-220

Keyword(s):

Regression Analysis ◽

Data Sources

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Analisis Keputusan Pembelian terhadap Lemang Batok Berdasarkan Kemasan, Cita Rasa, dan Harga

Economics, Business and Management Science Journal ◽

10.34007/ebmsj.v1i1.14 ◽

2021 ◽

Vol 1 (1) ◽

pp. 47-57

Author(s):

Lilinesia Lilinesia

Keyword(s):

Regression Analysis ◽

Linear Regression ◽

Multiple Linear Regression ◽

Research Method ◽

Linear Regression Analysis ◽

Multiple Linear Regression Analysis ◽

Quantitative Approach ◽

Data Sources ◽

Analysis Techniques ◽

A Value

This research was conducted with the aim of knowing whether the packaging affects the decision to purchase lemang batok in Tebing Tinggi City. And to find out whether the taste simultaneously influences the decision to buy lemang batoks in Tebing Tinggi Municipality. This is to determine whether the price has a partial effect on the decision to purchase lemang shells in Tebing Tinggi City. To find out whether, taste, and price affect the decision to buy lemang batok in Tebing Tinggi City. The research method uses a quantitative approach. This study uses multiple linear regression analysis techniques. Data sources are divided into two, namely primary and secondary. The results obtained (1) packaging has a significant effect, with the results of t count 3.077 t table with a value of 2.880 and a value of 0.003 0.05. (2) Taste has a significant effect, with the result of t count 5,678 t table with a value of 2,880 and a value of ,000 0,000 0.05. (3) Price also has a significant effect, with a negative t count result of 3.115 t table 2.880 and a value of 0.002 0.05. Packaging, taste and price have an effect simultaneously with the results of the f count 14.231 f table 2.71. Significance value 0.000 0.05.

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KAJIAN FAKTOR-FAKTOR YANG MEMPENGARUHI MOTIVASI BELAJAR GEOGRAFI DI SMA

GEOGRAPHIA : Jurnal Pendidikan dan Penelitian Geografi ◽

10.53682/gjppg.v2i1.1525 ◽

2021 ◽

Vol 2 (1) ◽

pp. 80-86

Author(s):

Hence Pantouw ◽

Maxi Tendean ◽

Paulus Robert Tuerah

Keyword(s):

Regression Analysis ◽

Multiple Regression Analysis ◽

Quantitative Methods ◽

Learning Motivation ◽

Data Sources ◽

Dominant Factor ◽

Student Interest ◽

Motivation To Learn ◽

Learning Factor ◽

Joint Contribution

This study aims to determine the contribution of the variable of student interest in learning to motivation to learn, the contribution of the variable of parents' attention to learning motivation, the contribution of the variable of student learning facilities to learning motivation, the contribution of the variable of geography learning to learning motivation, and the contribution of the four variables together to student's motivation to study. The research uses quantitative methods, the data sources come from observations, documentation, and questionnaires, then analyzed by multiple regression analysis. The results showed that the factors that influence students' learning motivation in geography are interest factors, parental attention, learning facilities, and geography learning. The interesting factor contributes to the motivation of 0.511. The parental attention factor contributed to the motivation of 0.694. The factor of learning facilities contributed to the motivation of 0.672. The geography learning factor contributed 0.514. The overall and joint contribution of the four variables to motivation is 0.752, and the rest is influenced by other factors that are not studied in the study. The dominant factor that affects learning motivation is the parent's attention factor, which is 0.694.

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