Statistical packages for social science version 19

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Sourced in United States

SPSS Statistics 19 is a comprehensive set of tools for data management, analysis, and presentation. It provides a wide range of statistical procedures to analyze and understand data. The software offers a user-friendly interface and a variety of advanced analytics capabilities.

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Statistical Package for Social Science version 19.0 Statistical Package for Social Sciences version 19.0 Statistical Package for Social Sciences 19.0 Statistical Package for Social Science (version Statistical Package for Social Sciences (version Statistical Package for Social Science package Statistical Packages for Social Sciences Statistical Package for Social Sciences Social Science Statistical Package Statistical Package Social Sciences

9 protocols using statistical packages for social science version 19

Comparative Analysis of Cardiovascular Metrics

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All statistical analysis was performed using Statistical Packages for Social Science version 19 (SPSS Inc., Chicago, IL, USA). Data were expressed as mean (standard deviation) for quantitative variables like age, weight, SBP, DBP, HR. Independent sample t-test and Mann-Whitney tests were applied to compare the mean/median difference between groups for age, weight. The paired t-test was used to compare within-subject effect for HR and BP. P < 0.05 was considered as significant.

Kashif S, & Hamid M. (2016). Efficacy of intravenous paracetamol on pressor response in patients undergoing cesarean section under general anesthesia. Journal of Anaesthesiology, Clinical Pharmacology, 32(2), 210-213.

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Statistical Analysis of Rotation Duration

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All statistical analysis was performed using Statistical Packages for Social Science version 19 (SPSS Inc., Chicago, IL). Median and interquartile range were computed for duration of rotation while frequency and percentage were computed for qualitative reply.

Minai F., Ul Haq M.I, & Afshan G. (2014). A survey of undergraduate anesthesia rotation in medical colleges of Pakistan. Journal of Anaesthesiology, Clinical Pharmacology, 30(1), 82-85.

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Statistical Analysis of Quantitative Data

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A statistical analysis was performed using the Statistical Packages for Social Science version 19 (SPSS Inc., Chicago, IL, USA). The mean and standard deviation were computed for quantitative variables.

Andleeb S., Yasir Bari M., Gill I., Urooj S, & Nausheen S. (2019). Incidence of Encephalitis in the Intensive Care Unit, a Tertiary Care Hospital, Pakistan: A 5-Year Retrospective Study. Turkish Journal of Anaesthesiology and Reanimation, 48(4), 288-293.

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Perioperative Complications in Neurosurgical Patients

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Data was analyzed using statistical packages for social science version 19 (SPSS Inc., Chicago, IL). Frequency and percentage was computed for qualitative observations like gender, comorbid conditions like diabetes mellitus (DM), hypertension (HTN), ischemic heart disease (IHD), Asthma, and perioperative complications. Mean and standard deviation was estimated for age, height, weight, BMI, duration of surgical procedure and estimated blood loss. The frequency and percentages were also calculated for AEs at T1, T2, T3 and T4. Stratification analysis was done to evaluate the relationship between age, gender, BMI, comorbid, type of procedure and blood loos with the frequency of AEs. Chi-square test was used to observe difference. P≤0.05 was considered as significant. The sample size was calculated on the basis of previous reported incidence of Post operative complications in neurosurgical patients; that is 54.5,8 (link) with 10% margin of error and 95% confidence interval.

Chandio M., Shafiq F, & Enam S.A. (2021). Frequency of early postoperative adverse events (AEs) in adult patients undergoing elective neurosurgical intervention at tertiary care center in Pakistan. Pakistan Journal of Medical Sciences, 37(4), 939-944.

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Analyzing Participant Responses via SPSS

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Responses of participants were exported from excel to statistical packages for social science version 19 (SPSS Inc., Chicago, IL) for analysis. All of these responses were compiled in tables and bar chart. Most of the questions were closed ended therefore frequency and percentages were reported. Due to large information supplementary tables and figure were also provided separately.

Haq M.I., Shafiq F, & Sheikh H. (2020). Potential Barriers amongst Health Care Professionals of Pakistan in managing COVID-19 patients. Pakistan Journal of Medical Sciences, 36(COVID19-S4), S17-S21.

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Postoperative Pain Management Analysis

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Statistical analysis was performed using the Statistical Packages for Social Science version 19 (SPSS Inc., Chicago, IL, USA). Mean and standard deviation were estimated for numeric characteristics of patients. Frequency and percentage were computed for anesthetic characteristics, surgical incision, analgesic technique and co-analgesia requirement, satisfaction of patients regarding postoperative pain management, and complication of patients. Chi-square test was applied to compare pain intensity, complication, and patient experience regarding postoperative pain management among analgesic techniques. P ≤ 0.05 was considered as significant.

Ismail S., Siddiqui A.S, & Rehman A. (2018). Postoperative pain management practices and their effectiveness after major gynecological surgery: An observational study in a tertiary care hospital. Journal of Anaesthesiology, Clinical Pharmacology, 34(4), 478-484.

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Demographic and Quantitative Data Analysis

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All statistical analysis was performed using Statistical Packages for Social Science version 19 (SPSS, Inc., Chicago, IL, USA). Demographic data were compared using Chi-square test. Quantitative data were compared using un-paired t-test. Statistical significance was considered if P < 0.05.

Gupta S., Mehta N., Mahajan A., Dar M.R, & Gupta N. (2017). Role of Oral Prednisolone in the Management of Postdural Puncture Headache after Spinal Anesthesia in Urological Patients. Anesthesia, Essays and Researches, 11(4), 1075-1078.

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Anesthesia Outcomes Statistical Analysis

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All statistical analysis was performed using Statistical Packages for Social Science Version 19 (SPSS Inc., Chicago, IL, USA). Qualitative variables such as morbidity, gender, American Society of Anesthesiologists (ASA) status, type of anesthesia, and surgery were presented as frequency and percentage while mean and standard deviation (SD) were computed for age.

Khan F.A., Khan S, & Afshan G. (2017). An analysis of perioperative adverse neurological events associated with anesthetic management at a Tertiary Care Center of a developing country. Journal of Anaesthesiology, Clinical Pharmacology, 33(1), 48-56.

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Epidural Failure Rate and Anesthesiologist Expertise

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Data were analyzed by statistical packages for social science version 19 (SPSS Inc., Chicago, IL). It was observed that some studies reported an 8% to 23% epidural failure rate.[7 (link)8 (link)9 (link)10 (link)] The sample size of 492 patients (approximate = 500) was included to estimate the expected epidural failure rate within a 2.5% margin of error on the basis of an 8% epidural failure rate. The outcome variable of the study was the failure rate of labor epidural as per defined criteria and the exposure variable was grades of anesthesiologists. The central tendency of the quantitative point estimates were reported as mean and standard deviation and qualitative point estimates were as frequency and percentage. A binary logistic regression was used to assess the association between the failure rate of labor epidural and grades of anesthesiologists. Odds ratio (OR) and 95% confidence interval (CI) were reported. P value ≤ 0.05 was considered significant.

Ismail S., Raza A., Munshi K, & Tabassum R. (2021). Failure rate of labor epidural: An observational study among different levels of trainee anesthesiologists in a university hospital of a developing country. Journal of Anaesthesiology, Clinical Pharmacology, 37(2), 210-215.

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