Studi Longitudinal Pada Analisis Data Gula Darah Pasien Diabetes melalui Principal Component Analysis

Multicollinearity is a relationship or correlation between predictor variables. Multicollinearity can also occur in longitudinal data, which is a combination of cross-section data and time-series data. The impact of multicollinearity causes the influence of the predictor variable on the response variable to be insignificant, the least-squares estimator, and the error to be sensitive to changes in the data. Therefore, the procedure to overcome multicollinearity uses the principal component analysis method. This study aims to model PCA longitudinal data regression with a fixed-effect model that is applied to blood sugar data of diabetic patients with a time span of January 2019 to July 2019 at Ibnu Sina Hospital Makassar City. The results of this study indicate that there are two main components formed from PCA longitudinal data regression modelling with a fixed-effect model. Obtained variable values are systolic blood pressure of -0.007, diastolic blood pressure of -0,016, the body temperature of -0.098, and platelets of 0.005 which affect blood sugar in patients with diabetes.

Pemodelan Data Kemiskinan di Provinsi Jawa Barat Menggunakan Regresi Spasial Data Panel

Persentase kemiskinan di Provinsi Jawa Barat masih tergolong cukup tinggi dan masih menjadi fokus perhatian pemerintah. Faktor-faktor yang memengaruhi kemiskinan penting untuk diketahui agar pemerintah mampu membuat suatu kebijakan yang tepat untuk menekan angka kemiskinan. Oleh karena itu, pada penelitian ini, dilakukan suatu analisis untuk mengetahui faktor-faktor yang memengaruhi tingkat kemiskinan di Provinsi Jawa Barat. Analisis pada penelitian ini menggunakan metode regresi spasial data panel karena diduga pada data kemiskinan di Provinsi Jawa Barat terdapat efek spasial dan unit amatan diamati pada jangka waktu tertentu. Model yang terbentuk dari analisis ini adalah Fixed Effect Spatial Error Model karena interaksi spasial yang terbentuk pada data kemiskinan di Provinsi Jawa Barat nyata pada error. Model ini juga berhasil menjadi model terbaik dibandingkan model lainnya berdasarkan kriteria nilai R-square terbesar. Analisis data kemiskinan di Provinsi Jawa Barat menggunakan metode regresi spasial data panel memperoleh hasil bahwa usia harapan hidup, pengeluaran per kapita disesuaikan, dan rata-rata lama sekolah berpengaruh secara signifikan terhadap persentase penduduk miskin di Provinsi Jawa Barat.

DAMPAK PENERIMAAN DAN PENGELUARAN PEMERINTAH DAERAH TERHADAP PENDAPATAN PERKAPITA ANTAR KABUPATEN JAWA BARAT

Penelitian ini bertujuan untuk menganalisis dampak penerimaan dan pengeluaran pemerintah daerah terhadap peningkatan pendapatan perkapita. Ruang lingkup penelitian yaitu seluruh Kabupaten di Jawa Barat dengan periode penelitian 2017-2020. Metode penelitian yaitu metode fixed effect panel data (Generalized Least Square) sebagai dasar perhitungan analisis variabel bebas terhadap variabel tidak bebas. Pendapatan perkapita merupakan variabel tidak bebas dalam penelitian ini, sedangkan variabel dana desa, pendapatan asli daerah, pengeluaran pemerintah dan jumlah penduduk sebagai variabel bebas. Hasil penelitian menjelaskan variabel dana desa, pendapatan asli daerah dan pengeluaran pemerintah mempengaruhi positif dan signifikan terhadap pendapatan perkapita. Sedangkan jumlah penduduk sebagai variabel kontrol berpengaruh negative terhadap pendapatan perkapita.

Hypermethylation of the RASSF1A gene promoter as the tumor DNA marker for nasopharyngeal carcinoma

Background RASSF1A is a tumor suppressor gene. The methylation of RASSF1A has been reported to be associated with nasopharyngeal tumorigenesis. However, the heterogeneity was high among different studies. A meta-analysis was performed to evaluate the value of RASSF1A methylation for the diagnosis and early screening of nasopharyngeal carcinoma. Methods Relevant articles were identified by searching the MEDLINE database. Frequency and odds ratio (OR) were applied to estimate the effect of CDH-1 methylation based on random-/fixed-effect models. The meta-analysis was performed by using MedCalc® software. Subgroup analyses were performed by test method, ethnicity, and source of nasopharyngeal carcinoma samples to determine likely sources of heterogeneity. Results A total of 17 studies, including 1688 samples (1165 nasopharyngeal carcinoma samples, and 523 from non-cancerous samples) were used for the meta-analysis. The overall frequencies of RASSF1A methylation were 59.68% and 2.65% in case-group and control-group, respectively. By removing the poor relative studies, the heterogeneity was not observed among the studies included. The association between RASSF1A gene methylation and the risk of nasopharyngeal carcinoma was also confirmed by calculating the OR value of 30.32 (95%CI = 18.22–50.47) in the fixed-effect model (Q = 16.41, p = 0.36,I 2 = 8.62, 95% CI = 0.00–45.27). Additionally, the significant association was also found between the methylation of the RASSF1A gene and the subgroups. Conclusions This is the first meta-analysis that has provided scientific evidence that the methylation of RASSF1A is the potential diagnosis, prognosis, and early screening biomarker for nasopharyngeal carcinoma.

The impact of factors on information sharing: An application of meta-analysis

Background Information sharing plays a key role in supply chain performance. According to previous individual studies, technology, trust, commitment, and uncertainty are four potential factors affecting information sharing. However, most studies focus on testing a positive relationship between each factor and information sharing. Therefore, it is necessary to evaluate the effect of each factor on information sharing. Objective To determine the accurate effect of factors on sharing information and propose key factors to support decision-makers in improving their information sharing. Data Correlation coefficients between factors are collected from 41 individual studies with a total of 8,983 samples on Google Scholar Methods Using the rank correlation test and Egger’s regression test to test publication bias. The meta-analysis method is used to perform analysis models, including fixed-effect, random-effect, and Hunter and Schmidt methods Results Commitment plays the most important role in information sharing when compared to technology, trust, and uncertainty. Commitment accounts for 19% in the Hunter and Schmidt method and 22% in both fixed-effect and random-effect models. In addition, the result indicates that there are around 50% of other factors that affect the efficiency of sharing information besides four factors in our studies. Conclusion Technology, trust, and commitment significantly affect information sharing, of which the impact of commitment on information sharing is strongest and should be a priority in improving the effectiveness of information sharing. Our study contributes two findings to literature in the field of supply chain information sharing: 1) certain confirming the important role of commitment on sharing information, and 2) the necessity of considering other factors besides these four elements.

Analisis Regresi Data Panel Pada Kemiskinan Provinsi Aceh Tahun 2016-2020

Kemiskinan menjadi salah satu indikator kesejahteraan pembangunan disuatu daerah. Semakin tinggi tingkat kemiskinan suatu daerah maka akan mengindikasikan bahwa kualitas pembangunan masyarakat di daerah tersebut rendah. Penelitian ini bertujuan untuk memodelkan dan mengetahui faktor-faktor yang mempengaruhi kemiskinan di provinsi Aceh tahun 2016-2020. Metode analisis yang digunakan adalah analisis regresi data panel dengan sumber data sekunder yang diperoleh dari badan pusat statistika (BPS). Hasil penelitian menunjukkan bahwa model yang sesuai dengan data kemiskinan provinsi Aceh tahun 2016-2020 adalah model regresi data panel dengan pengaruh tetap (Fixed effect model). Faktor-faktor yang signifikan mempengaruhi kemiskinan yaitu indek pembangunan manusia, angka kesakitan, dan laju pertumbuhan penduduk dengan nilai R squared yang tinggi sebesar 97.14 % .

Competitive Conditions in Nepalese Commercial Banks

This study aims to analyze the competitive conditions of commercial banks in Nepal. Competition is measured through structural and non-structural measures of bank competition. Data were taken from 21 commercial banks of Nepal using pooled sampling method, including five commercial banks based on the highest total assets and sixteen commercial banks using random sampling. Concentration ratio, Herfindahl-Hirschman Index, H-statistic and Lerner Index measures were used to assess the competitive position of Nepalese commercial banks. Panel data regression model with bank fixed effect and time fixed effect was employed to measure H-statistic and Lerner index. Findings showed the increasing pattern of capitalization and the decreasing trend of non-performing loan ratio, indicating that Nepalese commercial banks have a low possibility of loan default and, are more financially stable. It also showed the declining trend of bank concentration and HHI, suggesting that Nepalese commercial banks are losing their monopoly power and becoming more competitive in recent years. Competition in the loan market was found higher than deposit market competition. Banks have to pay special attention to loan portfolio management rather than deposit collection strategies. This study concludes that the competitive condition of Nepalese commercial banks is monopolistic. Therefore, appropriate strategies might be taken into action to sell financial products and services competitively.

Stock returns, oil prices and leverage: evidence from US firms

PurposeThis paper aims to investigate how the relation between stock returns of US firms and West Texas Intermediate (WTI) oil prices is affected by leverage from 1990 to 2020.Design/methodology/approachThis paper examines how the relationship between stock returns of US firms and WTI oil prices is affected by leverage from 1990 to 2020 using a fixed-effect model estimation framework.FindingsResults from the fixed-effect regression models suggest that leverage effects on stock returns are pervasive both in aggregate and cross-industry levels, while the mining industry is more sensitive. In addition to the positive oil price effects attenuated by leverage at the aggregate level, the authors observe stronger marginal effects of leverage only for the mining sector. Being more exposed to commodity prices, the positive effects of oil prices on stock returns in the mining sector are offset by large debt ratios. Asymmetries, effects of debt maturity structure and implications are also discussed.Research limitations/implicationsThis study is grounded on the contemporary cash flow claim of leverage NOT on the long-run effect of leverage considering cash flow constraints. The oil price increase is assumed to represent an advancement of the overall economy. This study does not capture the oil prices response to some other economic forces and vice-versa.Practical implicationsMining companies should therefore reduce the stock of debt with respect to their assets to make possible the “pass-through” from oil prices to the stock market.Originality/valuePreviously undocumented and the authors show that leverage reduces the total effect of oil prices on stock returns, consistent with the hypothesis. Asymmetric and debt maturity structures effects are also discussed.

Female Director and Agency Cost: Does board gender diversity at Indian corporate board reduce agency conflict?

We examined the presence of women directors in top-level management and their effect on principal-principal conflict (PP) and principal-agent conflict (PA) on the firms listed on Indian stock exchange using a panel model approach. For analysis purpose, this study covers the sample of 75 companies belonging to various industries and listed in Bombay Stock Exchange Index, has been studied over thirteen financial years, i.e. from year 2006 to year 2019. This study uses panel data analysis, i.e. fixed effect model and random effect model. The proportion and presence (dichotomous) of women directors on top level management board is taken as the independent variable. Principal-principal conflict measured by assets utilization ratio (AUR), and principal-agent conflict is been measured by dividend payout ratio (DPR), are taken as dependent variable in this study. The prime results of this study using panel data analysis, i.e. fixed effect (FE) and random effects (RE) estimation models point towards no significant impact of the female director (proportion and presence) on the firm’s agency cost (PP and PA).