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Spss 19.0 statistical

Manufactured by IBM
Sourced in United States

SPSS 19.0 is a software package for statistical analysis. It provides tools for data management, analytical reporting, and modeling. The core function of SPSS 19.0 is to enable users to analyze and interpret data through a variety of statistical techniques.

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256 protocols using spss 19.0 statistical

1

GBS Infection and Pregnancy Outcomes

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All statistical analyses were performed using SPSS 19.0 statistical software. Chi-square test was applied to estimate difference in clinical characteristics between late pregnant women with different GBS infection statuses. Spearman test was used to analyze the clinical correlations of GBS with pregnancy/neonatal outcomes. P < 0.05 was considered statistically significant in the present study.
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2

Statistical Analysis of Count and Measurement Data

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SPSS19.0 statistical software was used for data analysis. Count data were expressed as percentages and analyzed with Chi-squared test or Fisher exact probability analysis. Measurement data were expressed as median (P25, P75) and analyzed with Mann–Whitney U test, P < .05 was considered statistically significant.
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3

Statistical Analysis of Experimental Data

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Results were analyzed with SPSS 19.0 statistical software. The mean and standard deviation were expressed. One-way analysis of variance (ANOVA) and Newman-Keuls post hoc test were performed for statistical analyses. Statistically significant difference was defined as p < 0.05.
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4

Comparative Statistical Analysis of Experimental Data

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Values from three replications were utilized to calculate means and standard deviations. For all comparisons, significant differences between the groups were expressed as follows: *P<0.05 and **P<0.01. All data were submitted to multiple comparisons by t-test and one-way analysis of variance and analyzed by SPSS 19.0 statistical software for Windows.
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5

Statistical Analysis of Experimental Data

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Statistical analysis was performed using SPSS 19.0 statistical software. The count data were expressed as mean ± standard deviation (x ± s). The comparison between multiple groups was performed by one-way analysis of variance, and P < 0.05 indicated that the difference was statistically significant.
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6

Statistical Analysis of Experimental Data

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Statistical analysis was performed using SPSS19.0 statistical software. Numerical data were expressed as mean ± SD. The categorical variables were assessed by χ2 or Fisher's exact test. Comparisons of the quantitative variable were analyzed by Student's t-test or one-way analysis of variance. The Spearman's rank correlation test was used to determine the correlation. P < 0.05 was considered to indicate a statistically significant difference.
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7

Statistical Analysis of Experimental Data

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The data were presented as means ± S.D. from at least three independent experiments and evaluated through the analysis of ANOVA followed by student’s t-test. The values of P < 0.05 were considered statistically significant. The analyses were performed using SPSS 19.0 statistical software.
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8

Exploring Cisplatin Resistance Mechanisms

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All data were processed using SPSS 19.0 statistical software. The correlation between CUEDC2 expression and cisplatin resistance was analyzed by chi-square test. The difference between two subgroups was analyzed by two independent samples t-test. Survival curves were constructed with the Kaplan-Meier product-limit method and compared by the log-rank test. To evaluate the independent prognostic factors associated with survival, multivariate Cox proportional hazards regression analysis was used. All statistical tests were two-sided and P values < 0.05 were considered to be statistically significant.
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9

Continuous Variables Statistical Analysis

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Continuous variables are described in average, median, and standard deviation. SPSS19.0 statistical software was used and χ2 test with multiple composition ratios were used. p < 0.05 was considered statistically different.
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10

Qualitative Analysis of Caregiver Burden

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Analysis of the data followed the “framework” approach. The first step of the analysis was to transcribe the audio-record, word for word. The researcher listened repeatedly to the audio-record and read the noted observations to correct the transcripts. After repeatedly reading the transcripts, a code frame was progressively established based on recurring viewpoints emerging from the data and the interview guideline. Every transcript was then coded systematically against the code frame. Codes were merged into categories and then these categories were organized into themes. Disagreements were discussed among the research team to reach a final consensus. The principal researcher revisited the main points of the findings with the participants and asked whether they were consistent with their experiences. The process of analysis was conducted in Chinese and the results were translated to English.
We used SPSS19.0 statistical software package to analyze the data from the ZBI questionnaire. We used descriptive statistics, independent sample t-test, analysis of variance of statistical method to analyze their burden level, with P < 0.05 for the statistically significant difference.
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