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Estimation of haemoglobin concentration in the tropics by means of oxyhaemoglobin solutions

WADSWORTH GR, LEE TS

Med J Malaya, 1955 Sep;10(1):87-91.
PMID: 13287498
Matched MeSH terms: Regression Analysis*
Fulltext A review of property mass valuation models

Ebrahim Jahanshiri, Taher Buyong, Abdul Rashid Mohd. Shariff

Pertanika Journal of Science & Technology, 2011;19(3):23-30.
MyJurnal

Mass valuation of properties is important for purposes like property tax, price indices construction, and understanding market dynamics. There are several ways that the mass valuation can be carried out. This paper reviews the conventional MRA and several other advanced methods such as SAR, Kriging, GWR, and MWR. SAR and Kriging are good for modeling spatial dependence while GWR and MWR are good for modeling spatial heterogeneity. The difference between SAR and Kriging is the calculation of weights. Kriging weights are based on the spatial dependence or so called the semi-variogram analysis of the price data whereas the weights in SAR are based on the spatial contiguity between the sample data. MWR and GWR are special types of regression where study region is subdivided into local sections to increase the accuracy of prediction through neutralizing the heterogeneity of autocorrelations. MWR assigns equal weights for observations within a window while GWR uses distance decay functions. The merits and drawbacks of each method are discussed.

Matched MeSH terms: Regression Analysis
Fulltext Applying the method of Lagrange Multipliers to derive an estimator for unsampled soil properties

Foong, Ng Set, Eng, Ch’ng Pei, Ming, Chew Yee, Shien, Ng Kok

Scientific Research Journal, 2014;11(1):0-0.
MyJurnal

Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this paper is an unbiased estimator. The partiality of the estimator with respect to the true value is zero. Hence, the estimated value will be equal to the true value of the soil property. It is also shown that the variance between the estimator and the soil property is minimized. Hence, the distribution of this unbiased estimator with minimum variance spreads the least from the true value. With this characteristic of minimum variance unbiased estimator, a high accuracy estimation of soil property could be obtained.

Matched MeSH terms: Regression Analysis
Fulltext Postural sway and shooting accuracy of skilled recurve archers

Muhamad Noor Mohamed, Azrul Hisham Azhar

Movement Health & Exercise, 2012;1(1):49-60.
MyJurnal

Postural movements potentially affect aiming stability in archery, thus contributing to chances of inconsistent hits. According to the expertisenovice paradigm, the factor that sets winners apart from ordinary athletes is the former’s ability to control minute changes in their performance. The
present study seeks to determine the relationship between postural sway and shooting performance amongst Malaysian skilled recurve archers. Twenty one skilled Malaysian archers participated in this study, where performance level was measured by rank tournaments International Archery Federation (FITA) score. Postural sway was assessed in terms of anterior deviation (positive value) and posterior deviation (negative value) using ZEPHYR Bio-Harness. Postural sway was analysed at the following three phases; (i) setup, (ii) aiming, and (iii) release. Participants shot 12 arrows to a 30-meter target. Data yielded a significant relationship between postural sway and shooting performance. The correlation coefficients between shooting performance and postural sway value for skilled archers ranged between (r = -0.021 to 0.248) with the highest correlation recorded at the release phase, with the lowest at the aiming phase. The setup phase showed the only anterior deviation throughout the test. During the setup and release phases, correlation between postural sway with shooting performance was significantly noted (p < 0.001). Multiple regression analysis showed that postural sway during the setup and release phases were the significant indicators for shooting performance, accounting approximately 17% and 24% of the variances respectively. In sum, the results indicate that reducing postural sway
during the release phase can increase shooting performance of skilled archery athletes, thus establishing a significant relationship between the postural sway value with shooting performance of skilled archers.

Matched MeSH terms: Regression Analysis
Fulltext Using bootstrapped quantile regression analysis for small sample research in applied linguistics: Some methodological considerations

Nikitina L, Paidi R, Furuoka F

PLoS One, 2019;14(1):e0210668.
PMID: 30640925 DOI: 10.1371/journal.pone.0210668

Quantitative applied linguistics research often takes place in restricted settings of an intact language classroom, workplace, phonetics laboratory or longitudinal sample. In such settings the samples tend to be small, which raises several methodological problems. The main aim of the current paper is to give a detailed explanation of methodological and practical implications inherent in a robust statistical method called bootstrapped quantile regression (BQR) analysis. Importantly for applied linguistics research, the BQR method could help to deal with methodological difficulties inherent in small sample studies. The current study employed a moderately small sample (N = 27) of students learning the Japanese language in a Malaysian public university. It examined the relationships between the students' language learning motivation (specifically, integrative orientation), the students' images or stereotypes about Japan and their global attitudes toward the target language country and its people. The findings indicated that there was a statistically significant relationship between the students' attitudes toward the target language country and their integrative orientation. In addition, these attitudes were found to be the most constant determinant of the integrative orientation. Besides the applied linguistics research, the BQR method can be used in a variety of the human sciences research where a sample size is small.

Matched MeSH terms: Regression Analysis
Fulltext Development of Linear Regression Model for tile waste generation in Malaysian construction industry

Siti Hafizan Hassan, Hamidi Abdul Aziz, Mohd Samsudin Abdul Hamid, Siti Rashidah Mohd Nasir, Suhailah Mohamed Noor

ESTEEM Academic Journal, 2019;15(2):11-23.
MyJurnal

The effect of unmanageable construction waste is an unstable land settlement and groundwater pollution. In addition to environmental pollution, construction waste could incur construction cost. The most construction waste is the material used at sites and tile is also a part of the waste generated in construction. The objectives of this study are to determine the tile waste generated in construction stages and linear regression analysis for the amount of tile waste generated. The method used in this study was the Linear Regression Model. The regression model established in the sample data reported an R2 value of 0.793; therefore, the model can predict approximately 79.3% of the factor (area) of tile waste generation. The linear regressions can be applied as tools to predict the tile waste generated at construction sites and help the contractor to track the sources of missing waste.

Matched MeSH terms: Regression Analysis
Flux model development and synthesis optimization for an enhanced GO embedded nanocomposite membrane through FFD and RSM approach

Abdul Wahab MS, Abd Rahman S, Abu Samah R

Heliyon, 2020 Nov;6(11):e05610.
PMID: 33305039 DOI: 10.1016/j.heliyon.2020.e05610

A two-level full factorial design was used to analyze several factors involved in PSF-GO-Pebax thin film nanocomposite membranes development. Permeate flux was chosen as a single response for four possible factors: Pebax selective layer concentration, amount of GO load to Pebax selective layer, Pebax-GO selective layer thickness, and amount of GO load to PSF substrate. The study is aimed at factors interaction and contribution towards the highest permeation flux via FFD and RSM approach. R2 obtained from the ANOVA is 0.9937 with Pebax concentration as the highest contributing factor. Pebax concentration-amount of GO load to PSF substrate is the only interaction contributing to the highest flux. A regression analysis concluded the study with model development and an optimized condition for the membrane design.

Matched MeSH terms: Regression Analysis
Fulltext Effect of food experience on overall satisfaction: comparison between first-time and repeat visitors to Malaysia

Roozbeh, B.H., Ng, S.I., Boo, H.C.

International Food Research Journal, 2013;20(1):141-146.
MyJurnal

The attractiveness of food as tourism product has partly derived from the gastronomic aspect. The ingredients, the preparations, the end products, and the eating circumstances are cultural, educational, and entertaining. However, there is little research empirically demonstrates if there is a difference between first-time and repeat visitors in terms of food experience at destination, or how the various food experience attributes influence visitors’ overall satisfaction while visiting a destination. Hence, this study was undertaken to address the gap. Data were collected via on-site survey questionnaire administrated to a random sample of visitors at the Kuala Lumpur International Airport (KLIA) and various touristic areas around Kuala Lumpur. The results indicated significant differences between first-time and repeat visitors in terms of their food experience. In addition, multiple regression analysis revealed that traditional food preparation was an important factor to tourists’ overall satisfaction for both first-time and repeat visitors. In sum, the study is the first to examine the effect of food experience attributes on first time and repeat visitors separately

Matched MeSH terms: Regression Analysis
Fulltext The performance of classical and robust logistic regression estimators in the presence of outliers

Habshah, M., Syaiba, B.A.

Pertanika Journal of Science & Technology, 2012;20(2):313-325.
MyJurnal

It is now evident that the estimation of logistic regression parameters, using Maximum LikelihoodEstimator (MLE), suffers a huge drawback in the presence of outliers. An alternative approach is touse robust logistic regression estimators, such as Mallows type leverage dependent weights estimator(MALLOWS), Conditionally Unbiased Bounded Influence Function estimator (CUBIF), Bianco andYohai estimator (BY), and Weighted Bianco and Yohai estimator (WBY). This paper investigates therobustness of the preceding robust estimators by using real data sets and Monte Carlo simulations. Theresults indicate that the MLE behaves poorly in the presence of outliers. On the other hand, the WBYestimator is more efficient than the other existing robust estimators. Thus, it is suggested that the WBYestimator be employed when outliers are present in the data to obtain a reliable estimate.

Matched MeSH terms: Regression Analysis
Fulltext Turnbull versus Kaplan-Meier estimators of cure rate estimation using interval censored data

Bader Ahmad Aljawadi, Mohd Rizam Abu Bakar, Noor Akma

Pertanika Journal of Science & Technology, 2012;20(2):243-255.
MyJurnal

This study deals with the analysis of the cure rate estimation based on the Bounded Cumulative Hazard (BCH) model using interval censored data, given that the exact distribution of the data set is unknown. Thus, the non-parametric estimation methods are employed by means of the EM algorithm. The Turnbull and Kaplan Meier estimators were proposed to estimate the survival function, even though the Kaplan Meier estimator faces some restrictions in term of interval survival data. A comparison of the cure rate estimation based on the two estimators was done through a simulation study.

Matched MeSH terms: Regression Analysis
Correlation between numbers of cells in human dental pulp and age: Implications for age estimation

Hossain MZ, Daud S, Nambiar P, Razak FA, Ab-Murat N, Saub R, et al.

Arch Oral Biol, 2017 Aug;80:51-55.
PMID: 28371626 DOI: 10.1016/j.archoralbio.2017.03.018

OBJECTIVE: The aim of this study was to investigate correlations between dental pulp cell count of odontoblasts, subodontoblasts and fibroblasts and age, within different age groups. Formulation of regression equations using the dental pulp cell count for predicting age was attempted.
DESIGN: Eighty-one extracted teeth were grouped into two age groups (6-25 years, 26-80 years). The teeth were demineralized and histological sections were prepared for cell count. Regression equations were generated from regression analysis of cell count and tested for age estimation.
RESULTS: The number of dental pulp cells were found to increase until around the third decade of life and following this, the odontoblasts and subodontoblasts cell numbers began to decline while the fibroblasts seemed to remain almost stationary. The Pearson correlation test revealed a significant positive correlation between the cell number for all type of cells and age in the 6-25 years group (r=+0.791 for odontoblasts, r=+0.600 for subodontoblasts and r=+0.680 for fibroblasts). In the 26-80 years age group, a significant negative correlation of the odontoblasts (r=-0.777) and subodontoblasts (r=-0.715) with age was observed but for fibroblasts, the correlation value was negligible (r=-0.165). Regression equations generated using odontoblasts and subodontoblasts cell number were applicable for age estimation. The standard error of estimates (SEEs) were around±5years for 6-25 years and±8years for 26-80 years age groups. The mean values of the estimated and chronological ages were not significantly different.
CONCLUSIONS: A significant correlation between the cell count of odontoblasts and subodontoblasts with age was demonstrated. Regression equations using odontoblasts and subodontoblasts cell number can be used to predict age with some limitations.

Matched MeSH terms: Regression Analysis
Fulltext Preliminary study on the effects of sample density in activities determination of 137Cs using gamma spectrometry counting system

Yii, Mei Wo, Zaharudin Ahmad

Journal of Nuclear and Related Technologies, 2005;2005(2):41-46.
MyJurnal

Gamma Spectrometry Counting System requires similar counting geometries for the calibration source, reference material and samples. The objectives of this study were to find out the effects of the sample density on 137 Cs activities measurement and propose reasonable corrections. Studies found that the activity of the samples is decreasing when the density of samples increased. Therefore, in order to have a more accurate estimation of samples activities; density corrections should be done either by performs mathematical corrections using equation or by increasing the expanded uncertainty when sample densities deviated from calibration source.

Matched MeSH terms: Regression Analysis
Fulltext Analysis of turnover intention among manufacturing technicians in electronic industry

Abdul Rashid Ismail, Wan Normeza Wan Zakaria

Journal of Advanced Research Design, 2017;37(1):1-8.
MyJurnal

This study aims to examine the influences of the plan to further study, career growth
and discriminatory treatment on turnover intention among technicians in electronic
industry in Malaysia. The objectives are: (i) To identify the relationship between the
plan to further study and turnover intention among factory technicians, (ii) To identify
the relationship between career growth and turnover intention among factory
technicians, and (iii)To identify the relationship between discriminatory treatment
factors and turnover intention among factory technicians. The population involved in
this study were the manufacturing technicians at an electronic factory. Survey
questionnaires were used to collect data. A total of 110 questionnaires were analyzed.
Pearson correlation coefficient and regression analysis were used to measure the
degree of relationship between variables. The findings showed that all independent
variables; plan to further study, career growth and discriminatory treatment, were
positive moderately correlated with turnover intention.

Matched MeSH terms: Regression Analysis
Fulltext Inventory management improvement suggestion through time-series forecasting for financial service company

Adipriyana, Raditianto, Rosmahaida Jamaludin, Hayati Habibah Abdul Talib

Journal of Advanced Research Design, 2018;49(1):7-14.
MyJurnal

Management is consistently facing fast-flowing and lots of changes in business, including in the inventory management. Especially for fast-moving inventories, the correct stocking, controlling, checking and safety stock calculation is highly needed to have an exquisite inventory management and to reduce the possibility of running out of inventory which leads to unavailability to meet the demand. One of the ways to overcome this is by doing an excellent and appropriate forecasting. Therefore, the objective of this concept paper is to analyse and recommend tools to improve inventory management using the appropriate time-series forecasting method. The firm studied in this study is serving its employees as customers that demand the routine items including stationeries and other routine products to support their job as auditors and consultants for its client. However, there are occasions when there is out-of-stock situation for fast-moving items, especially in the peak season period. Furthermore, the firm is only applying replenishment based on the used inventories from the previous month. Therefore, this study suggests to eliminate out-of-stock items situation by applying precaution initiatives such as time-series forecasting. This study is planned to employ 10 time-series forecasting methods such as moving average, exponential smoothing, regression analysis, Holt-Winters analysis, Seasonal analysis and Autoregressive Integrated Moving Average (ARIMA) using Risk Simulator Software. By simulating those methods, the most appropriate method is selected based on the forecasting accuracy measurement.

Matched MeSH terms: Regression Analysis
Detection of Influential Observations in Principle Component Regression

Mokhtar b. Abdullah

Sains Malaysiana, 1996;25.

Multicollinearity that may exist among explanatory variables in a regression model can make the regression coefficients insignificant and difficult to interpret. Principal component regression (PCR) is an effective way for solving multicollinearity in regression analysis. The existence of multicollinearity mayor may not be induced by the presence of influential observations. This paper discusses some diagnostic methods for identifying influential observations in the PCR. A data set on water quality of New York Rivers was considered to illustrate the methods.
Multikolinearan yang wujud di kalangan pembolehubah penerang dalam model regresi boleh menyebabkan pekali regresi tidak bererti dan sukar untuk ditafsirkan. Regresi komponen utama (PCR) merupakan cara yang berkesan bagi menyelesaikan masalah multikolinearan dalam analisis regresi. Kewujudan multikolinearan mungkin disebabkan oleh data terpencil yang berpengaruh. Kertas ini membincangkan beberapa kaedah pengecaman bagi mengenalpasti data berpengaruh dalam PCR. Data tentang kualiti air di beberapa batang sungai di New York digunakan untuk memperihalkan kaedah pengecaman yang disarankan.

Matched MeSH terms: Regression Analysis
Pengaruh kepimpinan LMX terhadap tingkah laku kewarganegaraan keselamatan dalam kalangan bukan eksekutif

Abdullah HM, Khairudin R, Fatimah wH

Jurnal Psikologi Malaysia, 2014;olume 28:88-97.

This study was carried out to determine the influence of LMX towards the SCB worker dimension in a national automotive company in Malaysia. There were 360 respondents from the automotive company involved in this study. Data collected from respondents were analysed using descriptive (demographic frequencies) and inferential statistics (correlation and regression analysis). The results showed that one of the four independent variables has a positive influence on SCB. In terms of the demographic factors, none of the variables (age, gender and period of service) made any significant difference on LMX and SCB, except the position category. Further suggestions regarding LMX and SCB are discussed based on the findings.

Matched MeSH terms: Regression Analysis
Effects of fine-scale pattern of dwarf bamboo on understory species diversity in Abies faxoniana forest, Southwest, China

Wang YJ, Shi XP, Peng Y, Tao JP, Zhong ZC

Sains Malaysiana, 2012;41:649-657.

Dwarf bamboo is recognized as a significant determinant of the structure and dynamics in temperate forests. Quantitative relationships between the abundance (density and coverage) of dwarf bamboo, Fargesia nitida, and micro-environments, species diversity on the floor were estimated in an Abies faxoniana pure forest in southwest China. Understory microenvironmental conditions (daily differences temperature and moisture, RPPFD under bamboo layer and ground cover) changed dramatically with the bamboo density. Stepwise multiple regression analyses indicated that abundance of F. nitida was mainly correlated with canopy characteristics and disturbance factors in the A. faxoniana pure forest. All richness indices decreased significantly with the bamboo density and RPPFD under bamboo layer. Importance values (IV) of understory species in different bamboo densities and Detrended canonical correspondence analysis (DCCA) indicated three understory plant groups, resistant to high bamboo abundance (Group A), resistant to intermediate bamboo abundance (Group B) and sensitive to bamboo abundance (Group C). These groups mainly responded to abundance of bamboo and RPPFD under bamboo layer, resulted from the integration of characteristics of bamboo, canopy and topography factors. Different bamboo abundance had different influences on understory species diversity and groups. Dense F. nitida condition (> 10 culms/m2) had significant negative effect and 0-5 bamboo condition had not significant negative effect on understory species diversity in A. faxoniana forest. We suggest the fine-scale analysis on effects of bamboo abundance should be taken account into considering in heterogeneous patches in process of the succession and regeneration of natural forests.

Matched MeSH terms: Regression Analysis
A monte carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern

Habshah Midi, Bagheri A, Rahmatullah Imon A

Sains Malaysiana, 2011;40:1437-1447.

Outliers in the X-direction or high leverage points are the latest known source of multicollinearity. Multicollinearity is a nonorthogonality of two or more explanatory variables in multiple regression models, which may have important influential impacts on interpreting a fitted regression model. In this paper, we performed Monte Carlo simulation studies to achieve two main objectives. The first objective was to study the effect of certain magnitude and percentage of high leverage points, which are two important issues in tending the high leverage points to be collinearity-enhancing observations, on the multicollinarity pattern of the data. The second objective was to investigate in which situations these points do make different degrees of multicollinearity, such as moderate or severe. According to the simulation results, high leverage points should be in large magnitude for at least two explanatory variables to guarantee that they are the cause of multicollinearity problems. We also proposed some practical Lower Bound (LB) and Upper Bound (UB) for High Leverage Collinearity Influential Measure (HLCIM) which is an essential measure in detecting the degree of multicollinearity. A well-known example is used to confirm the simulation results.

Matched MeSH terms: Regression Analysis
Fulltext Statistical estimators as an alternative to standard deviation in weighted euclidean distance cluster analysis

Dalatu, Paul Inuwa, Habshah Midi

Pertanika Journal of Science & Technology, 2018;26(4):1823-1836.
MyJurnal

Clustering is basically one of the major sources of primary data mining tools. It makes
researchers understand the natural grouping of attributes in datasets. Clustering is an
unsupervised classification method with the major aim of partitioning, where objects in the
same cluster are similar, and objects which belong to different clusters vary significantly,
with respect to their attributes. However, the classical Standardized Euclidean distance,
which uses standard deviation to down weight maximum points of the ith features on the
distance clusters, has been criticized by many scholars that the method produces outliers,
lack robustness, and has 0% breakdown points. It also has low efficiency in normal
distribution. Therefore, to remedy the problem, we suggest two statistical estimators
which have 50% breakdown points namely the Sn and Qn estimators, with 58% and 82%
efficiency, respectively. The proposed methods evidently outperformed the existing methods
in down weighting the maximum points of the ith features in distance-based clustering
analysis.

Matched MeSH terms: Regression Analysis
Predictions of biochar production and torrefaction performance from sugarcane bagasse using interpolation and regression analysis

Chen WH, Hsu HJ, Kumar G, Budzianowski WM, Ong HC

Bioresour Technol, 2017 Dec;246:12-19.
PMID: 28803060 DOI: 10.1016/j.biortech.2017.07.184

This study focuses on the biochar formation and torrefaction performance of sugarcane bagasse, and they are predicted using the bilinear interpolation (BLI), inverse distance weighting (IDW) interpolation, and regression analysis. It is found that the biomass torrefied at 275°C for 60min or at 300°C for 30min or longer is appropriate to produce biochar as alternative fuel to coal with low carbon footprint, but the energy yield from the torrefaction at 300°C is too low. From the biochar yield, enhancement factor of HHV, and energy yield, the results suggest that the three methods are all feasible for predicting the performance, especially for the enhancement factor. The power parameter of unity in the IDW method provides the best predictions and the error is below 5%. The second order in regression analysis gives a more reasonable approach than the first order, and is recommended for the predictions.

Matched MeSH terms: Regression Analysis

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