Multivariate Regression Analysis Using Statistics with R

2013 ◽  
Vol 765-767 ◽  
pp. 1572-1575
Author(s):  
Xiu Min Li
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Multivariate Regression ◽  
Multivariate Regression Analysis ◽  
Processing Data

Multiple regression analysis is a useful model in econometrics. It can be applied in many fields. Statistics software plays an important role in processing data. This paper gives a method to use R, constructs regression model, and explains the result.

scholarly journals Prognosis of chronic lymphocytic leukemia: a multivariate regression analysis of 325 untreated patients

Blood ◽  
1987 ◽  
Vol 69 (3) ◽  
pp. 929-936 ◽  
Author(s):  
JS Lee ◽  
DO Dixon ◽  
HM Kantarjian ◽  
MJ Keating ◽  
M Talpaz
Keyword(s):  
Alkaline Phosphatase ◽  
Uric Acid ◽  
Regression Analysis ◽  
Lactate Dehydrogenase ◽  
Chronic Lymphocytic Leukemia ◽  
Regression Model ◽  
Multivariate Regression ◽  
Risk Groups ◽  
Multivariate Regression Analysis ◽  
Lymphocytic Leukemia

Three hundred twenty-five previously untreated patients with chronic lymphocytic leukemia were analyzed to identify significant prognostic factors for survival. Univariate analysis identified the following characteristics associated with survival: (1) clinical characteristics: age, race, sex, performance status, lymphadenopathy, and hepatosplenomegaly; (2) hematologic parameters: WBC count, absolute lymphocyte and granulocyte counts, hemoglobin level, and platelet count; and (3) biochemical parameters: serum albumin, calcium, uric acid, lactate dehydrogenase, alkaline phosphatase, BUN, and creatinine. Multivariate regression analysis in a randomly selected training subset of 217 patients demonstrated that the combination of uric acid, alkaline phosphatase, lactate dehydrogenase, external lymphadenopathy, and age had the strongest predictive relation to survival time. The resulting model was validated in the remaining independent subset of 108 patients and led to classification of patients into low, intermediate, and high-risk groups with five-year survival rates of 75%, 59%, and 14%, respectively, and with distinctively different annual mortality rates (P less than .01). Both the regression model and Rai staging were highly effective in identifying risk groups among the entire patient population (P less than 0.001). Overall the regression model was superior to Rai staging in defining prognostic risk groups. In addition, it was able to separate patients into significantly different risk categories within each Rai stage, thus improving on the prognostic prediction of individual patients with chronic lymphocytic leukemia.

scholarly journals Prognosis of chronic lymphocytic leukemia: a multivariate regression analysis of 325 untreated patients

Blood ◽  
1987 ◽  
Vol 69 (3) ◽  
pp. 929-936 ◽  
Author(s):  
JS Lee ◽  
DO Dixon ◽  
HM Kantarjian ◽  
MJ Keating ◽  
M Talpaz
Keyword(s):  
Alkaline Phosphatase ◽  
Uric Acid ◽  
Regression Analysis ◽  
Lactate Dehydrogenase ◽  
Chronic Lymphocytic Leukemia ◽  
Regression Model ◽  
Multivariate Regression ◽  
Risk Groups ◽  
Multivariate Regression Analysis ◽  
Lymphocytic Leukemia

Abstract Three hundred twenty-five previously untreated patients with chronic lymphocytic leukemia were analyzed to identify significant prognostic factors for survival. Univariate analysis identified the following characteristics associated with survival: (1) clinical characteristics: age, race, sex, performance status, lymphadenopathy, and hepatosplenomegaly; (2) hematologic parameters: WBC count, absolute lymphocyte and granulocyte counts, hemoglobin level, and platelet count; and (3) biochemical parameters: serum albumin, calcium, uric acid, lactate dehydrogenase, alkaline phosphatase, BUN, and creatinine. Multivariate regression analysis in a randomly selected training subset of 217 patients demonstrated that the combination of uric acid, alkaline phosphatase, lactate dehydrogenase, external lymphadenopathy, and age had the strongest predictive relation to survival time. The resulting model was validated in the remaining independent subset of 108 patients and led to classification of patients into low, intermediate, and high-risk groups with five-year survival rates of 75%, 59%, and 14%, respectively, and with distinctively different annual mortality rates (P less than .01). Both the regression model and Rai staging were highly effective in identifying risk groups among the entire patient population (P less than 0.001). Overall the regression model was superior to Rai staging in defining prognostic risk groups. In addition, it was able to separate patients into significantly different risk categories within each Rai stage, thus improving on the prognostic prediction of individual patients with chronic lymphocytic leukemia.

scholarly journals A Study on the Prediction of Daily Snowmelt Depth using Multiple Linear Regression

2020 ◽  
Vol 20 (6) ◽  
pp. 311-321
Author(s):  
YeoungRok Oh ◽  
Gyumin Lee ◽  
Kyung Soo Jun ◽  
Wooyeon Sunwoo ◽  
SeungWoo Baek ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Snow Depth ◽  
Meteorological Data ◽  
Multiple Regression Model ◽  
Independent Variables ◽  
Fresh Snow ◽  
Humidity Range

In this study, daily snowmelt was predicted using observed meteorological data and multiple regression analysis. Five observation stations (located in Daegwallyeong, Gwangju, Seosan, Mokpo, and Jeonju) were selected to analyze fresh snow depth from 2000 to 2010. The dependent variable used in the multiple regression analysis was daily snowmelt depth, and the independent variables were fresh snow depth, diurnal temperature range, temperature interception, diurnal humidity range, humidity intercept, and solar radiation. Seventy percent of the total observed data was used to develop a multiple regression model and the regression model was verified using the 30% of remaining data. The adjusted R-squared and Root Mean Square Deviation (RMSE) were used to examine the developed regression model. As a result, the adjusted R-squared was higher than 0.769 (except Daegwallyeong); thus the developed model represented well the daily snowmelt depth. Even Jeonju had an adjusted R-squared of 0.869. Also, the RMSE in all of the five stations was lower than 2.5 cm. The lowest value in Seosan was 1.7 cm. From the two types of verification, the developed multiple regression model was judged to be suitable to predict the daily snowmelt depth. However, multicollinearity should be explained, as rapid increases in temperature and sustained high temperature could not be reflected in the model. Therefore, if the limitations were resolved in further research, the model could be used to predict the amount of daily snowmelt depth more reliably.

scholarly journals The Influence of Learning Method and Learning Style of the Ability for English Students of Akademi Pariwisata Satu Nusa Bandar Lampung

2020 ◽  
Vol 5 (2) ◽  
pp. 41-51
Author(s):  
Rara Agustin
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Learning Style ◽  
Learning Method ◽  
Processing Data ◽  
English Students

The purpose of this research is to know and analyze the effects of learning method and learning style to influence the ability for English students of Akademi Pariwisata Satu Nusa Bandar Lampung. This research consisted of forty two respondent on Akademi Pariwisata Satu Nusa Bandar Lampung. In the methode do applying for collecting data by documentation study, observation and interview, and then the angket. For processing data using the multiple regression analysis to know relation indefendent variable (X1) method of learning and (X2) learning style to influence defendant variable (Y) ability of English students. Furthermore in its data analysis using SPSS Statistics 24 program. In addition, the results of these research appeared that by significant 0, 05 for two side test 2, 5% and n =42 to obtain t statistics’s table 2,023. But t from testing  2,731 for method of learning, and 3,119 for learning style therefore method of learning  and learning style has positive significant influences for the ability of English students of Akademi Pariwisata Satu Nusa Bandar Lampung. This result could be explained that testing of  F and testing of t statistics. F statistics’s table 3,238 but F testing 9,141 by statistics’s table. Therefore,  it can be conclude that there is any positive significant influences on English students’ ability of Akademi Pariwisata Satu Nusa Bandar Lampung.

The Empirical Study for National Determinant of Coffee Consumption

2014 ◽  
Vol 962-965 ◽  
pp. 1275-1278
Author(s):  
Chao Cheng Chung ◽  
Sze Ting Chen ◽  
Yen Yen Chen ◽  
Chung Yi Chung
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Multivariate Regression ◽  
Stepwise Regression ◽  
Electricity Consumption ◽  
Coffee Consumption ◽  
Economic Factor ◽  
Multivariate Regression Analysis ◽  
Average Life ◽  
Average Life Expectancy

This study analysis the national determinant in the coffee consumption. The final dataset includes 136 countries and nine variables, coffee consumption, GDP, the number of vehicles per capita, and electricity consumption, education, tourism spending, literacy, drinking water quality population density, and the average life expectancy which are all collected from global international independent institutes. In our research, we use the regression model to interpret what the determinant can predict the coffee consumption in a country. We further discussed our research in descriptive statistics analysis, stepwise regression analysis, control some variables, and also multivariate regression analysis. The result showed that the economic factor, i.e. the GDP, play the most important role in the coffee consumption and significantly. The R-Sq (Adj) for this regression model was 59.1%.

scholarly journals Pengaruh Insentif dan Disiplin Terhadap Prestasi Kerja Pegawai (Studi Kasus pada Inspektorat Provinsi Sumatera Selatan)

2017 ◽  
Author(s):  
Hendra Hadiwijaya
Keyword(s):  
Regression Analysis ◽  
Job Performance ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Work Performance ◽  
A Value ◽  
Processing Data ◽  
Dominant Influence

Job performance is the result of employee working in quality and quantity in performing their duties in accordance with the responsibilities given to him. This study aims to identify and analyze the influence of variables incentives and discipline partially and simultaneously on job performance Employee Inspectorate of South Sumatra province. The present study sample as many as 51 samples. This research analyzes using multiple regression analysis using SPSS for Windows version 20 for processing data. These results indicate the effect of incentives and disciplinary partially on employee job performance, each by 2.37 and 5.32 as well as a significant value. of 0.000 and 0.020 is less than 0.05, which means that the variable incentive and discipline partially positive and significant impact on job performance Employee in the Inspectorate of South Sumatra province and the influence of incentives and disciplines simultaneously to job performance Employee of 70.125 with significant value of 0.000, this shows the influence of incentives and discipline against the employee work performance together towards the achievement Employees working in the Inspectorate of South Sumatra province. Variable discipline has dominant influence on employee job performance in the Inspectorate of South Sumatra province with a value of 5.32 and sig. 0,000

scholarly journals Pengaruh Kualitas Pelayanan Account Representative (Ar) Terhadap Kepuasan Dan Kepatuhan Wajib Pajak Badan (Studi Pada Perusahaan Makanan Di Kota Malang)

2013 ◽  
Vol 4 (2) ◽  
pp. 119
Author(s):  
Ajeng Rachma Pertiwi ◽  
M. Khoiru Rusydi
Keyword(s):  
Quality Of Service ◽  
Regression Analysis ◽  
Data Analysis ◽  
Regression Model ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Significant Influence ◽  
Quality Service

AbstractThe objective of this research is to know influence between account representative quality service as an evidence of administration modernization of taxation with the taxpayer satisfaction and the taxpayer compliance. Quality of service was measured based on tangibles, reliability, responsivness, assurance, and empathy responder. Method applied for data analysis used multiple regression analysis. Analysis result of regression model I indicated tangibles, reliability, responsivness, assurance, and empathy variables had no a significant influence to satisfaction of taxpayer. While partially regression model II indicated that tangibles, reliability, responsivness, and empathy variables didn't have significant effect to taxpayer compliance, and assurance variable has an significant effect to taxpayer compliance. This thing means that taxpayer compliance was influenced by assurance variable. If satisfaction and compliance of taxpayer increased, receiving of tax will increase.

scholarly journals Persepsi dan Pemahaman Pelaku Usaha Terhadap Berlakunya Standar Akuntansi Keuangan Entitas Mikro Kecil Menengah di Kota Bandung

2021 ◽  
Vol 6 (2) ◽  
pp. 72-85
Author(s):  
Kasir
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Study Data ◽  
T Test ◽  
Primary Data ◽  
F Test ◽  
The City

The purpose of this study was to determine the perception and understanding of MSME centers business on the application of SAK EMKM starting Januari 1, 2018 at the MSME Business Center in Bandung. In this study the data used are primary data, that is data obtained directly from the object under study. Data obtained through questionnaires to several MSME business center operastors int the city of Bandung. Sampling was carried out using the Sloving formula, resulting in 336 MSME respondents. The regression model used in this study to use Multiple Regression Analysis. The results of this study by t test (partial) showed that the perception of MSME actors did not effect the implementation of SAK EMKM and the understanding of MSME actors influenced the implementation of SAK EMKM. While the F test (simultaneous) showed that the perception and understanding of MSME actors influence the implementation of SAK EMKM.

Throughput Estimation Model of Cluster Tool in Semiconductor Manufacturing

2019 ◽  
Vol 814 ◽  
pp. 196-202
Author(s):  
Ying Mei Tu
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Semiconductor Manufacturing ◽  
Production Equipment ◽  
Process Time ◽  
Main Stream ◽  
Estimation Model ◽  
Cluster Tools

Semiconductor manufacturing management system was developed and grown up over the past decades. In order to increase the product yield and enhance the production productivity, cluster tools became the main stream in modern wafer fabrication factories which occupies over 50% of production equipment. Generally, cluster tools are integrated by several components including robots, vacuum chambers (Load locks) and single-wafer process chambers in a module and can be treated as a small factory. The throughput estimation before recipe release is very difficult. However, it is necessary and important for the planning activity. In this work, a throughput estimation model for cluster tools is proposed. The Multiple Regression Analysis is applied to develop a set of throughput estimation equations. A simulation model of cluster equipment including 3 single-wafer process chambers are built to get the historical throughput data for the regression analysis. From the Multiple Regression Analysis, it reveals that different numbers of recipes processed in the same time have to develop different regression model. The major factors in the regression model include numbers of load ports and process time of each recipe. Furthermore, a set of recipes are used to test the accuracy of estimation. Based on the testing results, they revealed that the MAPE is under 3% and the estimation model is accepted in practice to forecast the throughput of recipes for the planning activities.

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