Showing 2 results for Faghihzadeh
Ar Soltanian, S Faghihzadeh, A Gerami, D Mehdibarzi, J Jing Cheng,
Volume 6, Issue 1 (20 2010)
Abstract
Background & Objectives: In clinical trials some of participants do not take assignment treatment. Intention-to-treat (ITT) is one of the strategies to analyze of clinical trials with control. ITT estimation will be invalid and incorrect to show of treatment effects in case of existing non-compliance in participants. In this study we adjusted noncompliance effect to compare of active treatment and placebo.
Methods: To demonstrate efficiency of proposed model, a dataset of crossover clinical trial with 42 patients with knee osteoarthritis was used. To estimate the non-compliance’s effect adjusting at comparison of treatment effects, we use mean of compliance proportion at periods in sequences. The parameters were estimated by maximum likelihood method. ( could you ask authors to have a look at what they wrote and compare with Farsi version)
Results: The results show that baseline variables distributions like duration of disease, severity of disease, age and sex, were not significant (p>0.05). The standard error estimation of treatment effects ( ) based on adjusted model were less than standard model (0.09 and 0.12, respectively). In addition, likelihood ratio statistics based on adjusted model were less than standard model (1177.7 versus 1205.1).
Conclusion: Based on estimation of standard errors and likelihood ratio statistics at adjusted and standard models, we observe that adjusted model is more efficient than standard model.
F Mohammadzadeh, S Faghihzadeh, Ar Baghestani, M Asadi Lari , Mr Vaez Mahdavi, J Arab Kheradmand , Aa Noorbala, Mm Golmakani, Aa Haeri Mahrizi , R Kordi,
Volume 9, Issue 1 (5-2013)
Abstract
Background & Objectives: Chronic pain is one of main public and individual health problems and its epidemiological understanding needs reliable estimates of prevalence. The aim of this study was to investigate the epidemiology of chronic pain in all 368 neighborhoods of Tehran using small area estimation method.
Methods: The pain section from the second round of Urban HEART data from a selected individual of 23457 households in Tehran using a multistage randomized cluster sampling in 2011, were analyzed. In order to obtain reliable estimates for chronic pain prevalence at neighborhood level, a generalized linear mixed model and hierarchical Bayesian approach were used and the reliability of the estimates were evaluated.
Results: The average of estimated prevalence of chronic pain in neighborhoods of Tehran was 25.5% and a large heterogeneity was observed in its prevalence in neighborhoods of Tehran. Prevalence of chronic pain was significantly higher in married housewives, retirees and pensioners and was significantly associated with age, educational status, depression and anxiety (P<0.05). The reliability of Bayesian method was confirmed by evaluation methods in this analysis.
Conclusion: These results demonstrate prevailing amount of chronic pain at neighborhood-level in Tehran, which warrants careful attention to prevention, treatment, and rehabilitation by health care professionals.
