Background: Small P-values have been conventionally considered as evidence to reject a null hypothesis in empirical studies. However, there is widespread criticism of P-values now and the threshold we use for STATISTICAL SIGNIFICANCE is questioned. Methods: This communication is on contrarian view and explains why P-value and its threshold are still useful for ruling out sampling fluctuation as a source of the findings. Results: The problem is not with P-values themselves but it is with their misuse, abuse, and over-use, including the dominant role they have assumed in empirical results. False results may be mostly because of errors in design, invalid data, inadequate analysis, inappropriate interpretation, accumulation of Type-I error, and selective reporting, and not because of P-values per se. Conclusion: A threshold of P-values such as 0. 05 for STATISTICAL SIGNIFICANCE is helpful in making a binary inference for practical application of the result. However, a lower threshold can be suggested to reduce the chance of false results. Also, the emphasis should be on detecting a medically significant effect and not zero effect.

Background and Aim: When analyzing the gain-frequency response of a hearing aid, data can be analyzed both clinically and STATISTICALly. This study aimed to investigate and compare the gain-frequency responses using STATISTICAL and clinical analyses under active digital noise reduction (DNR-on) and inactive digital noise reduction (DNR-off) conditions. Methods: The gain-frequency responses of a hearing aid for one of the most well-known commercial digital hearing aid manufacturers were measured using the FP35 hearing aid analyzer (Frye Electronics Inc., USA) by presenting two types of signals (digital speech and composite noise) at input levels of 65 and 80 dB SPL under the DNR-on and DNR-off conditions. Data analysis was performed both STATISTICALly (using Wilcoxon signed rank test) and clinically (using 3 dB difference criterion). Results: A STATISTICALly significant difference was found in the gain-frequency responses for all speech and noise input levels between the two conditions,while a clinically significant difference was observed only at noise input levels of 65 and 80 dB SPL. Conclusion: For analyzing the hearing aid performance, both clinical and STATISTICAL analyses should be considered.

The misinterpretation and misuse of p-value have been increasing for decades. In March 2016, the American STATISTICAL Association released a statement to warn about the use and interpretation of p-value. In this study, we provided a definition and discussion of pvalue and emphasized the importance of its accurate interpretation.

Introduction: Determining the amount of changes produced in the treatment of chronic pain patients is important. STATISTICAL tests of SIGNIFICANCE are usually used for this purpose. Although important, the use of STATISTICAL tests of SIGNIFICANCE in determining treatment improvements is associated with a number of limitations. To overcome these limitations, investigators have recommended using clinical SIGNIFICANCE to determine whether or not the treatment outcome is clinically significant.Method: Chronic pain patients from a pain clinic (57) were selected, using a convenience sampling method. These patients completed twice, a series of questionnaires with a 4-week interval: Pain-Self-Efficacy Questionnaire, Depression Anxiety Stress Scales, Multidimensional Pain Inventory, Physical Disability Questionnaire and Short form Health Survey. Pearson correlations were calculated between the scores of the patients obtained over the 4-week interval. These test-retest coefficients were used to establish a reliable change index for the two measures of pain self-efficacy and depression of the 11 chronic pain patients treated with cognitive behaviour therapy. STATISTICALly significant changes of the pain self-efficacy and depression were examined, using paired sample t-tests.Results: The results of tests of STATISTICAL SIGNIFICANCE provide evidence of STATISTICALly significant improvements at post-treatment in both measures of pain self-efficacy and depression. The results of a reliable change index (as one of the measures of clinical SIGNIFICANCE) documented that 9 of the 11 patients on the pain self-efficacy variable and 8 of the 11 patients on the depression variable achieved clinically significant gains.Conclusion: While STATISTICAL tests of SIGNIFICANCE provide little or no information regarding the variability in treatment response from person to person, tests of clinical SIGNIFICANCE go beyond this limitation and indicate who achieved clinically significant change.

In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of STATISTICAL energy analysis. Correct estimation of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the STATISTICAL energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound estimation.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

Background: The aim of this investigation is to evaluate the histologic results of biopsy in women with atypical squamous cells of undetermined SIGNIFICANCE (ASCUS) cytologic diagnosis.Materials and Methods: We reviewed a series of cases with ASCUS pap smears from March 1999 to Feb 2002 in Imam Khomeini Hospital (n= 104), Who had cervical biopsy indirected colposcopy (103) and in Onec endocervical biopsy obtained without colposcopy. In 60 patients before colposcopy and biopsy repeat pap smear was tabled.Results: Biopsy revealed 28.8% SIL (14 LSIL and 16 HSIL),1 invasive carcinoma and 1 endometrial carcinoma. Pap smear repeated for 60 women before colposcopy examination, which 7 (11.7%) of them were normal. ASCUS persisted in 45 cases (75%) and 8 cases (13.3%) turned out to be SIL (6 LSIL, 2 HSIL) of 7 normal repeat smear, 2 marked as LSIL by biopsy. In colposcopic examination 22 of 103 (21.4%) had normal view which one of them was LSIL histologically.Conclusion: Based on these findings, it seems immediate colposcopy and directed biopsy are appropriate procedures for management of ASCUS and to detect underlying SIL.