Statistical analysis was performed as described previously [35 (link)]. Briefly, SPSS 11.5 Statistical Software was used for statistical analyses. Asterisks (p ≤ 0.05) labeled statistical significance. The results are shown as means ± SD from independent experiments as indicated in figure legends. One-way ANOVA was used to evaluate differences between control and experimental conditions.
Spss 11.5 statistical software
Manufactured by IBM
Sourced in United States
SPSS 11.5 is a statistical software package developed by IBM. It provides tools for data analysis, including descriptive statistics, regression analysis, and statistical modeling.
Automatically generated - may contain errors
Lab products found in correlation
26 protocols using spss 11.5 statistical software
1
Statistical Analysis of Experimental Data
2
Statistical Analysis of Experimental Data
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SPSS 11.5 Statistical Software was used for statistical analyses. In order to determine the most suitable statistical test, the data were evaluated with several statistical tests. First, the Kolmogorov Smirnov Test was used to determine if the data were normally distributed. Then, a one way analysis of variance (ANOVA) test was used to check the homogeneity of the variance of the data. For the data fulfilling the parametric test assumptions, the ANOVA test was used to compare the groups. Otherwise, non-parametric statistical tests (a Mann-Whitney U test was used for pairwise comparisons and a Kruskal-Wallis test was used to compare multiple groups) were used. For all of the tests, the significance level was taken as 0.05.
3
Statistical Analysis of Experimental Data
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Data were expressed as the mean ± standard deviation and analyzed by analysis of variance followed by the least significant difference test. P<0.05 was considered to indicate a statistically significant difference. Statistical analyses were performed with SPSS 11.5 statistical software (SPSS, Inc., Chicago, IL, USA).
4
Triplicate Measurement Statistical Significance
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All measurements were made in triplicate and each experiment was performed on three separate occasions; the results are expressed as the average of the three parallel assays. A Student's t-test was computed to determine the statistical significance of the results. Differences were judged to be statistically significant when p<0.05. Statistical analysis was conducted using SPSS 11.5 statistical software.
5
Factors Influencing Severe Vivax Malaria
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In order to identify factors related to poor outcome of severe vivax malaria, individual patient’s data from all case reports, case series, letter to editors, and correspondences were input to SPSS 11.5 Statistical Software (SPSS Inc., Chicago, USA). Qualitative demographic data (e.g., gender, nationality, severity sign, country of infection, clinical and laboratory parameters time point of severe manifestation, treatment outcome, etc.) were analyzed using the frequency, percentage, and Chi-squared test with 95%CI. Differences among quantitative variables such as age, temperature, systolic blood pressure, diastolic blood pressure, pulse rate, days of fever, hemoglobin, leukocyte count, and platelet count between two groups were analyzed by an independent sample T test or Mann Whitney U test upon the distribution of the data.
6
Statistical Analysis of Continuous and Categorical Data
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Excel 2007 worksheet (Microsoft, Redmond, WA, USA) was used to input case information for data collation, and Statistical Package for Social Science (SPSS) 11.5 statistical software (SPSS Inc., Chicago, IL, USA) was used for data statistics. Shapiro-Wilk test was used to test the normal distribution of the continuous data. Variables satisfying the normal distribution were described by mean ±standard deviation (SD), otherwise, they were presented as the median (interquartile range, IQR). The categorical variables in this study were described as frequencies and percentages, and chi-square test was further used to compare their distribution differences. A two-sided P<0.05 indicates that the difference is statistically significant.
7
Statistical Analysis of Experimental Data
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Statistical analyses were performed with SPSS 11.5 Statistical software (SPSS Inc.) and statistical significance was set at P < 0.05 or P < 0.01. Data was presented as the mean ± SD. As the normality test by Kolmogorov-Smirnov test (K-S test) was passed, data was analyzed by using the Student’s t-test for comparison between two groups and one-way ANOVA for multiple groups followed by Fisher’s least significant difference (LSD) test, otherwise, by using Kruskal-Wallis H test.
8
Variance Analysis of Research Findings
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All the data are presented as mean ± standard deviation (SD). Variance analysis and F-tests for results were performed using SPSS11.5 statistical software (SPSS Inc., Chicago, IL, USA). P < 0.05 was considered statistically significant.
9
Statistical assay
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All data were displayed by mean ± standard deviation (SD) and produced by SPSS11.5 statistical software (SPSS Inc., Chicago IL, USA). Variance analysis was performed for the comparison of multiple groups. Group-group comparison was carried out with the Student-Newman-Keuls method (SNK), and a P <0.05 was considered a statistically significant difference.
10
Literature Search and Data Analysis
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Two authors conducted the literature search, study selection, and data extraction independently. Disagreements were resolved by discussion and consensus was met through a third party. SPSS 11.5 statistical software was used for data analyses (Chicago, IL, USA). Descriptive statistics procedures calculated frequency and percentage.
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