Patient characteristics and clinical outcomes were assessed using descriptive analyses, with the mean (standard deviation) and median (interquartile range) presented for quantitative variables and the frequency (percent) presented for qualitative variables. The comparison of characteristics and clinical outcomes between groups A and B were analyzed using twosample t-tests or Mann-Whitney U tests for quantitative variables and chi-square tests or Fisher’s exact test for qualitative variables. p-values are presented for all statistically significant variables. All statistical analyses were performed using the SPSS software package for Windows version 19.0 (IBM, Chicago, IL, USA). All tests were 2-sided, and p-values <0.05 were considered to indicate statistical significance.
Spss software package for windows version 19
Manufactured by IBM
Sourced in United States
SPSS software package for Windows version 19.0 is a comprehensive statistical analysis tool. It provides a wide range of data analysis and management capabilities, including data manipulation, statistical modeling, and reporting. The software is designed to work on the Windows operating system and is suitable for both individual and enterprise-level use.
Automatically generated - may contain errors
Lab products found in correlation
10 protocols using spss software package for windows version 19
1
Statistical Analysis of Clinical Outcomes
2
Prevalence and Factors of Internet Addiction
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
A summary of demographic and baseline characteristics was constructed using descriptive analysis; the mean, maximum, minimum, and SD for quantitative variables, and the frequency and percentage for qualitative variables. Prevalence of IA with respect to the status of AD was analyzed using χ2 tests or Fisher’s exact test. The logistic regression analyses were performed for IA and confounders (sex, age groups, hypertension, and diabetes mellitus) to calculate the odds ratio (OR) and 95% CI without considering any interactions. One of the co‐authors, a medical statistician, was tasked with supervision of the overall analytics procedure. All statistical analyses were performed using SAS Enterprise Guide 6.1 M1 (SAS Institute Inc., Cary, NC) and SPSS software package for Windows version 19.0 (IBM, Armonk, NY). All tests were 2‐sided, and P values <0.05 were deemed statistically significant.
3
Epidemiological Analysis of Atopic Dermatitis and Vitiligo in Ménière's Disease
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
A summary of demographic and baseline characteristics was constructed using descriptive analysis; the mean, maximum, minimum and standard deviation (S.D.) for quantitative variables and the frequency and percentage (%) for qualitative variables. Prevalence of atopic dermatitis (AD) and vitiligo, with respect to the status of Ménière disease (MD), was analysed using χ2 tests. One of the co-authors, a medical statistician, was tasked with supervision of the overall analytics procedure. All statistical analyses were performed using SAS Enterprise Guide 6.1 M1 (SAS Institute Inc., Cary, NC, United States) and IBM SPSS software package for Windows (version 19.0, Chicago, IL, United States). All tests were two-sided and p-values less than 0.05 were deemed statistically significant.
4
Evaluating Pain Scale Effects on Sample Size
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The sample size was calculated based on a previous study (Shebib et at., 2019 (link)) and taking into account the pain scale. At a significance level of 0.05 and a statistical power of 95%, the calculated total number of participants was 20. Considering a 10% dropout rate, the final number of participants was set to 23. Mean values were compared using the Mann–Whitney U tests. A generalized linear model was used to compare daily PA and EMG device–obtained data. A repeated-measures two-factor analysis of variance was performed in addition to multiple comparisons in case of a statistically significant difference. Pearson coefficients were used for correlation analyses. Statistical analysis was performed using the IBM SPSS software package for Windows (version 19.0, Chicago, IL, USA). Statistical significance was set at p < .05.
5
Fungicide Efficacy Evaluation Protocol
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Statistical analysis of the data was performed with the SPSS software package for Windows version 19.0 (SPSS Inc., Chicago, IL, USA). Percentages were converted into Bliss angular values before analysis. Differences in the mean values of percentage of germination, germ tube size, lag phase, growth rate, inhibition of growth, and incidence of disease were tested by one-way analysis of variance and separated by Tukey’s honestly significant difference test (p ≤ 0.050).
6
Comparative Safety Alert Analysis
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Descriptive statistics (counts and percentages) were used to characterize the variables assessed in this study. To compare the characteristics of alerts issued by AEMPS with those issued by the EMA (mainly by the PRAC), the Pearson chi-square or Fisher’s exact test for categorical variables was used. A bilateral p-value <0.05 was used to determine statistical significance.
All statistics were performed using the SPSS software package for Windows version 19.0 (SPSS Inc., Chicago, Ill).
All statistics were performed using the SPSS software package for Windows version 19.0 (SPSS Inc., Chicago, Ill).
7
Comparison of Bladder Outcomes in Patients
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Statistical analyses were performed using the SPSS software package for Windows version 19.0 (SPSS Inc., IL, USA). Continuous variables were expressed as means ± standard deviation, while categorical variables were expressed as percentage and frequency. The occurrence rates of BOD and PUR were compared by Pearson's Chi-square test between two groups. Shapiro-Wilk W test was used to detect if the data fitted normal distribution in each group. The time to spontaneous micturition, urine volume, and amount of intravenous fluids between the two groups were compared by two-sample t-test if the data followed normal distribution; otherwise, Mann-Whitney U test was used. The frequency of adverse events was analyzed between the two groups using Fisher exact test. All reported P values were two-sided, and P < 0.05 was considered statistically significant.
8
Statistical Analysis of Experimental Data
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The data were statistically analyzed using an SPSS software package for Windows version 19.0 (SPSS Inc., Chicago, IL, USA). Differences in the mean values of parameters were tested by oneway analysis of variance and separated by Tukey’s honestly significant difference test (P < 0.05).
9
Statistical Analysis of Research Data
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Results were analyzed statistically using an SPSS software package for Windows version 19.0 (SPSS Inc., Chicago, IL, USA). Differences in the mean values of parameters (±standard deviation) were tested by one-way analysis of variance (ANOVA) and separated by Turkey’s honestly significant difference test (p < 0.05).
10
Comparative Analysis of Physiological Markers
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The data were statistically analyzed using an SPSS software package for Windows version 19.0 (SPSS Inc., Chicago, IL, USA). Differences in the mean values of parameters were tested by one-way analysis of variance and separated by Tukey's honestly significant difference test (P < 0.05).
About PubCompare
Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.
We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.
However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.
Ready to get started?
Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required
Revolutionizing how scientists
search and build protocols!