Descriptive statistics were used to report on the collected data. Different denominators were used to report on the trial activity ‘data collection’, as detailed in the Results section. We performed χ2 tests to analyse potential correlations. The occurrence of decentralised and on-site conduct of the predefined trial activities was defined as binary outcome variables (yes/no), and the trial characteristics used for the comparisons—type of sponsor, region, trial phase, and time periods—were defined as categorial determinants. To correct for multiple comparisons, the statistical significance level was set at p=0.0019, following the Bonferroni method. That is, 0.05 divided by 26, the number of on-site and decentralised trial activities that were analysed. Statistical analyses were performed using IBM SPSS Statistics V.27.
Spss statistics v 27
Manufactured by IBM
Sourced in United States
SPSS Statistics V.27 is a data analysis software developed by IBM. It provides tools for data management, statistical analysis, and visualization. The software is designed to help users analyze and interpret complex data sets efficiently.
Automatically generated - may contain errors
Lab products found in correlation
Prism v9, by GraphPad (4 mentions)
Prism v5, by GraphPad (2 mentions)
Sas v9, by SAS Institute (2 mentions)
Matlab r2019a, by IBM (2 mentions)
Stata v 15, by StataCorp (1 mentions)
Prism v 9.0.0 for windows, by GraphPad (1 mentions)
Graphpad v 7, by GraphPad (1 mentions)
Nvivo software v12, by Lumivero (1 mentions)
G power v 3, by IBM (1 mentions)
Spss v27, by IBM (1 mentions)
Avizo 2020, by Thermo Fisher Scientific (1 mentions)
Avizo 2019, by Thermo Fisher Scientific (1 mentions)
Sas 9, by IBM (1 mentions)
Microsoft office excel, by IBM (1 mentions)
Metaboanalyst 5, by IBM (1 mentions)
Sigmaplot 14, by Grafiti LLC (1 mentions)
Prism v7, by GraphPad (1 mentions)
Prism v8, by GraphPad (1 mentions)
Prism v9.1.0 for mac, by GraphPad (1 mentions)
Prism 6, by GraphPad (1 mentions)
252 protocols using spss statistics v 27
1
Statistical Analysis of Decentralized Trials
2
Incarceration Outcomes Among Overdose Survivors
3
Parent-Set Technology Rules and Sleep
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Data were analysed using IBM SPSS Statistics v.27 and macro PROCESS v.3.5 (Model 1; [32 ]. Univariate general linear models (GLMs) were used to assess the links between parent-set rule groups and each of the sleep and sleepiness variables. GLMs were also used to assess the main effects of BtP and FoMO on sleep outcome variables/daytimes sleepiness. Least Significant Difference (LSD) adjusted pairwise post-hoc analyses allowed for comparisons between the three groups on each outcome variable. PROCESS was used to test for an interaction between BtP/FoMO and parent-set technology rule group on the sleep outcome variables/daytime sleepiness. Age and gender were controlled for in each model. Other covariates (e.g., caffeine, SES) were controlled for if they were significantly correlated to the outcome variable. Supplementary Table 1 presents zero order correlations between sleep variables, FoMO/BtP, daytime sleepiness, and covariates.
4
Stream pH and Vanuatubasis Presence
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In 2019, we sampled 53 streams. Fieldwork was conducted during the sunniest part of the day, between 09:00 and 14:00 h. At each surveyed location we recorded the pH using a High Accuracy pH meter (Dr. Meter, Union City, CA, USA). We recorded several points throughout the stream and the average pH was recorded. Data were only used in the final analysis if it met three criteria: (1) GPS coordinates and pH values were collected; (2) a minimum threshold of collecting time was met (>4.5 working hours); (3) the weather was favorable for odonate collecting (i.e., sunny) and wind and/or rain were not a confounding factor. In total, 42 rivers met our criteria and were included in the analysis (See Table S2 ). Tableau software (Salesforce, Mountain View, CA, USA) was used to depict locations surveyed and the range of pH levels across the islands. We performed an independent samples Mann–Whitney U test using SPSS Statistics v.27 (IBM, Chicago, IL, USA) to test for a significant correlation between pH-level and the presence or absence of Vanuatubasis.
5
Podiatric Rheumatology Clinic Assessment Data
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Microsoft Excel was used to analyse the extracted data and calculate descriptive statistics. All categorical data were described as frequencies and percentages, and continuous data were described as mean (SD). Service provision data were described at patient-level, in which the number of patients with the variable present during at least one appointment was used as the denominator. As an additional analysis, appointment-level data were also analysed, in which the total number of appointments across all patients was used as the denominator. The proportion of foot problems identified from the assessments performed was also calculated using both patient and appointment level data. To examine the differences in patient demographic and medical characteristics between patients who attended the AUT Podiatric Rheumatology Clinic and referred patients who did not attend a clinic appointment, Pearson’s Chi-squared and independent t-tests were used for categorical and continuous data, respectively. P-values less than 0.05 were considered statistically significant. All inferential analyses were conducted in IBM SPSS Statistics v.27.
6
Transcutaneous Vagus Nerve Stimulation Protocol
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Data were analysed using SPSS Statistics V.27 (IBM, Armonk, New York, USA). The Shapiro-Wilk test was performed to evaluate the normal distribution of the data. Results were expressed as absolute frequency, relative frequency, means and SD or median and IQR. The two-way Analysis of Variance for repeated measure was performed to compare the two baseline periods (T0 and T2) considering Time (T0 vs T2) as within subject factor and treatment schedule assigned by randomisation (A×B or B×A) as between subject factor. To compare the effect of tVNS and active control, the relative percent change (∆rel%) post-treatment with tVNS or with active control (T1 or T3) from baseline (T0 or T2) of NRS score, questionnaire scores and HRV indices was calculated [∆rel%=(post-baseline)/baseline*100]. The Student’s t-test for paired data was performed to compare the effect of tVNS and of active control on normally distributed parameters. The Wilcoxon signed-rank test was used to compare the effect of tVNS and of active control on non-normally distributed parameters. The χ2 test was performed to evaluate differences between the number of patients who experienced a clinically significant reduction in pain after tVNS and the number of patients who experienced a clinically significant reduction in pain after active control. A p value <0.05 was considered statistically significant.
7
Postoperative Complications Analysis
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The collected data formed our database and were analyzed using IBM SPSS Statistics V.27 software. Categorical variables are presented as counts and percentages, whereas continuous variables are presented as medians and ranges. Categorical independent variables were compared using the Χ2 test, and continuous variables were compared using the Mann-Whitney U test. Kaplan-Meier curves and log-rank tests were used to analyze the occurrence and timing of postoperative complications. There were no missing data. The level of statistical significance was set at p<0.05.
8
Online Survey of Daycare Providers
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Based on the data from the qualitative part of the inspiration phase (1A), a web-based online survey will be prepared using Qualtrics. The survey will be distributed, accompanied with a cover letter, to all accredited care providers specialised in day care (n=260). The survey will be pilot tested. In total, 24 respondents will fill in the pilot questionnaire: 8 DSPs working in day care, 8 healthcare students and 8 laymen. The data analysis will be carried out via IBM SPSS Statistics V.27 by the lead and junior researchers, under supervision of the senior researchers, and with assistance from the statistical expert. Final report will be written by the lead researcher (again with feedback from all authors).
9
Prognostic Factors in Metastatic Melanoma
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Univariate and multivariate Cox proportional hazards regression analyses were performed to assess the impact of baseline patient and tumor characteristics and therapeutic measures on PFS and OS. The following parameters were included into the univariate and multivariate analyses: sex, age, type of therapy, BRAF mutation status, ECOG performance status (ECOG-PS), serum LDH, number and maximal size of MBM, dexamethasone intake, application and type of radiotherapy for MBM (SRS and CRT), and surgery of MBM. OS was defined as time from start of systemic therapy until death or last patient contact (censored OS); PFS as time from start of systemic therapy until disease progression or last patient contact (censored PFS). Kaplan-Meier estimates were used for PFS and OS calculation; differences between groups were assessed by two-sided log-rank test. P values <0.05 were considered statistically significant. Patients with missing data were excluded from the respective analyses. Statistical analyses were performed with IBM SPSS Statistics V.27.
10
Comparative Analysis of Intervention Groups
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Categorical variables were reported as numbers and percentages. Descriptive data were presented as median and range. The IG and NIG were compared using the Mann–Whitney U test for continuous variables and chi-squared test for categorical variables. A value of p ≤ 0.05 was considered statistically significant. Calculations were performed using IBM SPSS Statistics v27 (IBM Corp, Armonk, NY, USA).
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