Spss statistics 17

A paper data collection instrument was developed, piloted and modified before use in the study. The instrument had three parts: (a) general information about the participants including socio-demographic variables and use of long-lasting insecticidal nets (LLINs); (b) clinical information (e.g. list of anti-malarial drugs used 28 days prior to data collection), laboratory data (e.g. level of haemoglobin, blood film result, parasite species and density) and the treatment given to the patient for a specific problem identified on the same date of diagnosis; and (c) detail of the medications taken by the HIV-positive patients and their CD4 count results.
Data was double entered using SPSS Statistics 17.0 (SPSS Inc., Chicago, USA). Any discrepancy between the two data sets was corrected by referring to the original paper form. The final single data set was cleaned and analyzed using STATA 11.0 (Statacorp, College Station, USA) and SPSS Statistics 17.0 (SPSS Inc., Chicago, USA). Data were organized and summarized using descriptive statistics, Chi square tests, and multivariate logistic regression; P values of <0.05 were considered statistically significant.

The dose–response curve generated from the series 1 experiments was analysed using logistic regression (SPSS Statistics 17.0) to estimate the concentrations lethal to 10%, 50% and 99% of the population (LC₁₀, LC₅₀, LC₉₉). For the series 2 experiments, two factor analysis of variance (ANOVA) was used to compare treatments (SPSS Statistics 17.0), using the data variables haemolymph osmolality, treatment and time (because these experiments were destructive, repeated measures ANOVA was inappropriate). Where there were significant interactions, multiple comparisons were done within levels of a factor using Tukey simultaneous tests (Minitab 15).

To compare the densities of the two Wolbachia strains in field mosquitoes in five regions (with different adult sizes), data were normalized to the expression of the host rps6 gene. Analyses were carried out using SPSS Statistics (17.0). Chi-square tests were performed to compare the prevalence of Wolbachia infections and one-way analysis of variance (ANOVA) was performed to compare densities of Wolbachia from different regions for normally distributed data using SPSS Statistics (17.0). Differences were considered statistically significant when P < 0.05. For better presentation of results, locA and locB were used to denote the densities of supergroup A and supergroup B, respectively, from regions with local dengue cases; impA and impB were used to denote the densities of supergroup A and supergroup B, respectively, from regions with only imported dengue cases; and noA and noB were used to denote the densities of supergroup A and supergroup B, respectively, from regions with no dengue cases.

Pearson’s product correlation analysis was performed using SPSS statistics 17.0 package to explore the relationship among DNRA rate, nrfA gene abundance, the diversity index and dominant environmental parameters. Linear regression analyses between DNRA rates and nrfA gene abundances were conducted using Origin 9.0 and SPSS statistics 17.0.

In this study, 2-year data of yield and net assimilation rate were presented, and the average of 2-year data was used for other indicators. Microsoft Excel 2019 was used to organize, calculate, and chart the data. IBM SPSS Statistics 17.0 (IBM Inc., Chicago, IL, USA) was used for statistical analysis. Analysis of variance was performed with IBM SPSS Statistics 17.0 (IBM Inc., Chicago, IL, USA) to test the effects of year, treatments (CN and PN), and N rates on grain yield, agronomic traits, N content, and nitrogen use efficiency. The DUNCAN method and paired t-test (p < 0.05) were used to determine the differences among the treatments.

The data have been reported as mean ± standard deviation (S.D.) from three independently performed experiments. Statistical analysis involving three or more groups was conducted using One-way ANOVA with SPSS Statistics 17.0 (IBM Corporations, New York, NY, USA), with significance set at p < 0.05. Conversely, statistical analysis for before and after treatments was determined by the paired t-test using SPSS Statistics 17.0 (IBM Corporations, New York, NY, USA), with significance levels denoted as * p < 0.05, ** p < 0.01, and *** p < 0.001.