linear regression

Linear-regression analysis is a well-known statistical technique that serves as a basis for understanding the relationships between variables. Its simplicity and interpretability render it the preferred choice in healthcare research, including vision science, as it enables researchers and practitioners to model and predict outcomes effectively. This article presents the fundamentals of linear-regression modeling and reviews the applications and interpretations of the main linear-regression analysis.

The primary objective of linear regression is to fit a linear equation to observed data, thus allowing one to predict and interpret the effects of predictor variables. A simple linear regression involves a single independent variable, whereas multiple linear regression includes multiple predictors. A linear-regression model is used to identify the general underlying pattern connecting independent and dependent variables, prove the relationship between these variables, and predict the dependent variables for a specified value of the independent variables. This review demonstrates the appropriate interpretation of linear-regression results using examples from publications in the field of vision science.

Simple and multiple linear regressions are performed, with emphasis on the correct interpretation of standardized and unstandardized regression coefficients, the coefficient of determination, the method for variable selection, assumptions in linear regression, dummy variables, and sample size, along with common mistakes in reporting linear-regression analysis. Finally, a checklist is presented to the editors and peer reviewers for a systematic assessment of submissions that used linear-regression models.

Medical practitioners and researchers should acquire basic knowledge of linear-regression such that they can contribute meaningfully to the development of technology by accurately interpreting research outcomes. Incorrect use or interpretation of appropriate linear-regression models may result in inaccurate results. Appointing an expert statistician in an interdisciplinary research team may offer added value to the study design by preventing overstated results.

Satisfaction with orthotic devices and services results in more significant orthotic usage. Evaluation of users’ satisfaction could enhance the quality of service delivery. This study aimed to identify the predictive value of demographic factors on users’ satisfaction with lower-limb orthoses and related services.

This study was a cross-sectional one. Ninety-seven users of lower-limb orthoses LLO participated in this cross-sectional study. Users’ satisfaction was evaluated with the Orthotic & Prosthetic Users’ Survey (OPUS). SPSS version 22 using linear regression test was used to identify which demographic variables explain variation in satisfaction with LLO and services.

According to linear regression, the variance of satisfaction with the device was significantly explained by the income level and the type of orthosis (P <0.05). However, the predictive value of these variables was relatively low (Adjusted R2 = 0.118). The results also showed that the variance of satisfaction with services was significantly explained by none of the dependent demographic variables (P> 0.05), and the prediction of the independent variable by the demographic variables was very low (Adjusted R2 = 0.063).

Orthotists should focus more on clients with low-income to acquire their satisfaction with devices and services. To satisfy their users, they also need to be more careful when making long orthoses such as Knee Ankle Foot Orthosis or Hip Knee Ankle Foot Orthosis.

Studying trends in observed rates provides valuable information in terms of need assessment, planning of programs and development indicators of each country. The purpose of the present study was to apply the regression model and the Fourier series in terms of predicting the trends in growth and mortality rate of coronavirus disease.

In this study, two linear analysis methods were used to predict the incidence and mortality rate of coronavirus disease in Iran and China. The methods used are linear regression and Fourier transform. The data used were collected by referring to the official media of the mentioned countries, the general form of which is a time series of the incidence and mortality rate in recent days and the model implemented to estimate the incidence and mortality rate for the coming days. Python programming language version 3.7 is used to implement models.

The results of this study show that the rates of coronavirus disease incidence and mortality are still increasing. Meanwhile, the Fourier transform-based analytical method is more accurate than the linear regression method and on the other hand, the accuracy of both algorithms for predicting mortality wasmuch higher than the prediction rate. This indicates that the mortality rate is higher than that of its linearity over time. The other point is that based on the results of this study, however, linear methods are very suitable for future prediction, due to the nature of epidemic diseases whose growth chart is nonlinear, linear methods cannot be used to predict the rate and mortality used in distant times.

The accuracy of the mathematics-based methods for predicting the trajectory of COVID-19 was really high. We predicted that the epidemics of COVID-19will be high during 10 days. If the data are reliable and there are no second transmissions, we can accurately predict the transmission dynamics of the COVID-19across the cities in China and Iran. The mathematics-inspired methods are a powerful tool for helping public health planning and policymaking.

This study aims to evaluate the effect of some factors, including birth weight, sex, age, waist circumference, family history of obesity, as well as some lifestyle factors as frequency of breakfast days and physical activity, on the body mass index among a nationally representative sample of Iranian children and adolescents by using bootstrapping regression.

This study was conducted as the third survey of a school-based surveillance system (CASPIAN-III study). Total participants were 5570 school students, aged 10-18 years, selected by multistage random cluster sampling from urban and rural areas of 27 provinces of Iran. Multiple linear regressions was used to evaluate the effect of various factors on obesity, but in our data the assumptions of this model violated, and possible solutions were not appropriate, therefore the bootstrapping regression based on the observations and errors resampling approaches was used as an alternative.

The tests of signifi cance showed that the effects of sex, age, waist circumference, family history obesity and frequency of breakfast days were clearly signifi cant (P < 0.001). The effect of vigorous level of physical activity was signifi cant in comparison to mild physical activity (P = 0.01). In comparison to low birth weight, medium and high birth weight had signifi cant effect on obesity.

Bootstrap method is preferable in linear regression because of some theoretical properties like having any distributional assumptions on the residuals and hence allows for inference even if the errors do not follow normal distribution or constant error variance.

Recently medical tourism as a new form of tourism has gained great popularity among the countries and a relatively large part of the world income is devoted to it. Since the high quality of service in the medical tourist's viewpoint has been a key factor in attracting and retaining them, the present study aimed to demonstrate which variables could affect the medical tourist's perspective about service quality.
We applied univariate analysis and multiple regression to explore the variables affecting medical tourists’ viewpoint about service quality they received. In order to measure thequality of service, we used SERVQUAL scale based on a gap model.
Findings: The findings showed nationality and type of therapy are the influential factors that affect patient's perspective.
Understanding the demographic characteristics of medical tourists helps the authorities to make better decisions and change their strategies in offering services in order to raise medical tourist's attraction and trust and also develop this type of industry.

The issues of patient safety and healthcare quality have become increasingly important around the world since the 1990s. Many hospitals manage to reduce the number of adverse events (AEs) that can threaten patient safety in healthcare organizations. Assessing the existing patient safety culture gives hospital management a clear vision of an organization’s strengths and weaknesses. The Safety Attitudes Questionnaire, with its good psychometric properties and great internal consistency, has been used extensively to assess the patient safety culture in healthcare organizations.
Physicians and nurses form the core staff of each organization. With different demographic variables, they might perceive patient safety culture differently. This study purposed to identify critical demographic variables from the viewpoints of physicians and nurses that significantly influence the patient safety culture in a regional teaching hospital in Taiwan.
Linear regression with forward selection was employed in this study to focus on all physicians and nurses using results of a 2015 internal survey in the case hospital. Ten demographic variables were the independent variables, and seven dimensions of the Chinese version of the Safety Attitudes Questionnaire were dependent variables.
Four out of 10 demographic variables had significant impacts on 6 out of 7 dimensions (with the exception of emotional exhaustion) from the Safety Attitudes Questionnaire. “Supervisor/manager” and “experience in position” followed by “age” were viewed by physicians and nurses as the most critical variables affecting the patient safety culture in this regional teaching hospital in Taiwan.
Assessing an organization’s current patient safety culture provides a significant value to improving patient safety. This study revealed that “supervisor/manager” and “experience in position” are the 2 most important demographic variables influencing the patient safety culture. Hospital management should take heed of the suggestions of staff members regarding these characteristics to continuously enhance their patient safety culture.

The present study attempted to investigate the emergence of especial skill in shooting with air gun at two skill levels (skilled, novice). The population studied here included all male and female shooters from the city of Semnan. The study was conducted on a sample of 40 shooters, consisting of two groups of women with the mean age of 21.33±2.26 and two groups of men with the mean age of 23.44±23.44, who displayed their shooting abilities with air guns from five points (8, 9, 10, 11, 12 meters) from the target. The test was conducted in 4 sets (with 15-minute rest intervals) each consisting of 5 blocks of 25 with 20 shots at each point (100 shots in all). The gap between each set was the resting time of 15 minutes. A significant difference was found between the actual and predictive scores in all groups (p<0.05): the differences found between actual and predictive scores were significant at P=0.012 for skilled male shooters, P=0.023 for novice male shooters, P=0.001 for skilled female shooters, and P=0.021 for novice female shooters. These findings of this study support the emergence of especial skill in all groups of air gun shooters.

Antipsychotic monotherapy or polypharmacy (concurrent use of two or more antipsychotics) are used for treating patients with psychiatric disorders (PDs). Usually, antipsychotic monotherapy has a lower cost than polypharmacy. This study aimed to predict the cost of antipsychotic medications (AM) of psychiatric patients in Iran. For this purpose, 790 patients with PDs who were discharged between June and September 2010 were selected from Razi Psychiatric Hospital, Tehran, Iran. For cost prediction of AM of PD, neural network (NN) and multiple linear regression (MLR) models were used. Analysis of data was performed with R 2.15.1 software. Mean ± standard deviation (SD) of the duration of hospitalization (days) in patients who were on monotherapy and polypharmacy was 31.19 ± 15.55 and 36.69 ± 15.93, respectively (P < 0.001). Mean and median costs of medication for monotherapy (n = 507) were $8.25 and $6.23 and for polypharmacy (n =192) were $13.30 and $9.48, respectively (P = 0.001). The important variables for cost prediction of AM were duration of hospitalization, type of treatment, and type of psychiatric ward in the MLR model, and duration of hospitalization, type of diagnosed disorder, type of treatment, age, Chlorpromazine dosage, and duration of disorder in the NN model. Our findings showed that the artificial NN (ANN) model can be used as a flexible model for cost prediction of AM.

To determine the associated factors of reflux duration, using quantile regression model. Reflux is one of the most prevalent gastrointestinal disorders. Statistical tools are widely used to assess the associated factors on reflux severity and frequency.Patients and A door to door questionnaire has been used to evaluate gastrointestinal symptoms including reflux and heartburn between May and December 2006 in Tehran. A total of 790 adult patients with gastrointestinal problems were selected using random sampling method. Among them 208 persons were found to have heartburn. A quantile regression was employed to assess the associated factors and the results were compared to linear regression and Cox semi parametric model. Heartburn duration had dramatically high negative skewness. Quantile regression analysis indicated significant increase in the given decile of heartburn duration associated with a unit increase in given patient characteristic containing sex, pain severity and pain after having some specific food. The results from linear regression and Cox model showed poor reliability in comparison to Quantile regression. The results have demonstrated that using quantile regression leads to better interpretation and richer inference about association between heartburn duration and patient characteristics.