Spss 19.0 statistical analysis software

Manufactured by IBM

Sourced in United States

SPSS 19.0 is a comprehensive statistical analysis software package developed by IBM. It provides a wide range of tools and functions for data management, analysis, and reporting. The software is designed to handle complex statistical analyses, including regression, correlation, and multivariate techniques. SPSS 19.0 is commonly used in fields such as social sciences, market research, and healthcare to analyze and interpret data.

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21 protocols using spss 19.0 statistical analysis software

Cerebral Blood Perfusion Comparison

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SPM8 was used to conduct the statistical analysis of the data of brain perfusion in the two groups and to present the results. An independent one-sample t-test was conducted for the healthy control and patient groups, with age and gender as the statistical covariates to produce the difference map of cerebral blood perfusion between the two groups. The results were superimposed onto a single T1 template using the xjView plug-in. The brain regions demonstrating statistical significance [P<0.05, with false discovery rate (FDR) correction and cluster size >30 voxels] were noted. Montreal Neurological Institute coordinate positioning (x, y, z; http://www.mcgill.ca/neuro/) and Brodmann area (http://www.talairach.org) identification were performed, and the intensity of the rCBF was recorded (presented by the statistical value ‘t’ in the t-test). The rCBF images of the healthy controls were first displayed layer by layer, followed by the cerebral perfusion images of the two groups displayed in layers.
SPSS 19.0 statistical analysis software (SPSS, Inc., Chicago, IL, USA) was used for the input, sorting and statistical analysis of the basic data for the two groups. The statistical analysis was performed using two independent sample t-tests, and P<0.05 was considered to indicate a statistically significant difference. The data are presented as the mean ± standard deviation.

Chen G., Bian H., Jiang D., Cui M., Ji S., Liu M., Lang X, & Zhuo C. (2016). Pseudo-continuous arterial spin labeling imaging of cerebral blood perfusion asymmetry in drug-naïve patients with first-episode major depression. Biomedical Reports, 5(6), 675-680.

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Statistical Analysis of Continuous and Categorical Variables

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SPSS 19.0 statistical analysis software (SPSS, Inc., Chicago, IL, USA) was used for statistical analysis. Continuous variables are presented as mean ± standard deviation (SD). Continuous and categorical variables were compared between groups using independent samples t-tests and Chi-square analysis. A P value of <0.05 was considered statistically significant.

Zhuo C.J., Bian H.M., Gao Y.J., Ma X.L., Ji S.Z., Yao M.Y., Zhai N., Sun X.H., Ma X.Y., Tian H.J, & Li G.Y. (2016). Nonspecific Effect of Stress on Brain Gray Matter Volume in Drug-naive Female Patients with First Depressive Episode. Chinese Medical Journal, 129(3), 279-283.

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Endoscopic Techniques for Invasion Depth

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Based on review of literature, the accuracy of magnifying NBI and chromoendoscopy in estimating invasion depth were assumed to be 85% and 95%, respectively.^{5 (link),14 (link)} To have 80% power to detect this 10% difference using 1-sided tests, with a type I error rate of 0.05, it was calculated that a total of 105 lesions would be needed.
Diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each technique were calculated in comparison with histological diagnosis. Differences of diagnostic performance between 2 modalities were evaluated using the McNemar test. P value < 0.05 was considered statistically significant. Kappa statistics were calculated to assess interobserver agreement for each modality. Kappa values <0.4, 0.41–0.6, 0.61–0.8, and >0.8 were regarded as representing poor, fair, good, and excellent agreement, respectively. SPSS 19.0 statistical analysis software was used for statistical analysis.

Zhang J.J., Gu L.Y., Chen X.Y., Gao Y.J., Ge Z.Z, & Li X.B. (2015). Endoscopic Diagnosis of Invasion Depth for Early Colorectal Carcinomas: A Prospective Comparative Study of Narrow-Band Imaging, Acetic Acid, and Crystal Violet. Medicine, 94(7), e528.

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Statistical Analysis of Experimental Data

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All data were expressed as the mean ± the standard error (SEM) and analyzed using the SPSS 19.0 statistical analysis software (SPSS, Inc., Chicago, IL, USA). Statistical significance was determined using an unpaired Student's t-test and one-way ANOVA followed by Dunett's post-hoc test. P<0.05 was considered to indicate a statistically significant difference.

Zhang Y., Zheng W., Shen K, & Shen W. (2018). ∆9-tetrahydrocannabinol inhibits epithelial-mesenchymal transition and metastasis by targeting matrix metalloproteinase-9 in endometrial cancer. Oncology Letters, 15(6), 8527-8535.

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Statistical Analysis of Experimental Replicates

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Each experiment was repeated five times with at least three replicates. SPSS 19.0 statistical analysis software (SPSS Inc., USA) was used to analyze data. Continuous variables are reported as means±SD and analyzed by one-way ANOVA. P<0.05 was considered to be significant.

Li Q., Yu Q., Na R, & Liu B. (2017). Etanercept protects rat cardiomyocytes against hypertrophy by regulating inflammatory cytokines secretion and cell apoptosis. Brazilian Journal of Medical and Biological Research, 50(6), e5868.

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Statistical Analysis of Demographic and Clinical Characteristics

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SPSS19.0 statistical analysis software was used for analysis. The differences in baseline demographic and clinical characteristics were analyzed by a chi-square test and t-test. The analyses of repeated measurement data used variance analysis of two-factor repeated measurement. Covariance analysis was used to adjust the confounding factors and determine the statistical significance of dependent variables. P < 0.05 was accepted as indicative of significant differences.

Liu L., Lu Y., Bi Q., Fu W., Zhou X, & Wang J. (2021). Effects of Different Intervention Time Points of Early Rehabilitation on Patients with Acute Ischemic Stroke: A Single-Center, Randomized Control Study. BioMed Research International, 2021, 1940549.

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Brain Perfusion Comparison Protocol

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SPM8 was used to conduct the statistical analyses of the brain perfusion data between the two groups and to demonstrate the final results. An independent one-sample t-test was conducted for the healthy control and patient groups. Age and gender were considered as the covariates to generate the difference map of cerebral blood perfusion between any two groups. The results were put into a single T1 template using the xjView software. Difference comparisons were corrected by the false discovery rate (FDR) method with a significance threshold of P < 0.05.
SPSS 19.0 statistical analysis software (SPSS, Inc., Chicago, IL, USA) was adopted for all statistical analyses of all data from the two groups. The statistical analyses were performed using two independent sample t-tests and P < 0.05 was considered to indicate a statistically significant difference. The data are presented as the mean ± standard deviation.

Wang S., Wang L., Jing P., Guo P., Zheng W., Li J, & Qian M. (2017). Aberrant patterns of brain cerebral blood flow in Chinese han first-episode drug-naïve depressive patients with and without a family history of depression. Oncotarget, 8(45), 79906-79913.

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Effects of Seed Treatments on Germination

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All data are expressed as mean ± standard error and the data were analyzed for normal distribution and homogeneity of variance. If data were not normally distributed and the variances were heteroscedastic, the Kruskal–Wallis non-parametric test was used [26 (link)]. Analyses of variances (ANOVA) was used to compare seed length, width and thousand seed weight of seeds before and after seeds imbibed water, to test the effects of temperature, light regime, and GA₃ concentration on germination of fresh seeds, to test the effects of storage time, temperature, and GA₃ concentration on germination of dry-storaged seeds, and to test the effects of osmotic potential on germination and seedling growth between mucilaged and demucilaged seeds. Tukey’s HSD test was used for multiple comparisons among treatments (P < 0.01). SPSS19.0 statistical analysis software was used during data processing and analyses (SPSS Inc., Chicago, IL, USA).

Zhang K., Zhang Y., Ji Y., Walck J.L, & Tao J. (2020). Seed Biology of Lepidium apetalum (Brassicaceae), with Particular Reference to Dormancy and Mucilage Development. Plants, 9(3), 333.

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Predictors of In-Hospital Mortality

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The study comprised 2 groups: survived and died. Quantitative variables were presented as mean ± standard deviation and categorical variables as percentages. Continuous variables were compared using the t test and categorical data were compared using the Fisher exact or Chi-square tests. Denominators represent only reported cases because missing data were not defaulted to negative. Variables with a marginal association with mortality (P < .10) were entered in stepwise multivariable logistic regression model for in-hospital mortality. Multivariate binary logistic regression analyses (backward-LR method) were performed to identify the predictors of in-hospital mortality. The odds ratio (OR) and the 95% confidence interval (CI) were also calculated. A value of P < .05 was considered significant. Data analysis was performed with the use of SPSS 19.0 statistical analysis software.

Zhang J., Cheng B., Yang M., Pan J., Feng J, & Cheng Z. (2019). Predicting in-hospital death in patients with type B acute aortic dissection. Medicine, 98(32), e16462.

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Statistical Analysis of Research Data

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The SPSS19.0 statistical analysis software (Chicago, IL, USA)was used in this study for data processing and analysis. Continuous variables were presented as the mean ± standard deviation. Continuous variables were described using median and interquartile range when they were in skewed distribution. Classified variables were presented as the absolute percentage. The Student's t-test was used for the continuous variables and χ² test was used for classified variables. P<0.05 suggested that the difference was statistically significant.

Ma J., Liu T, & Qu J. (2017). The effect of orbital implantation on peripheral blood melatonin and sex hormone levels in child patients with congenital eyeball dysplasia. Experimental and Therapeutic Medicine, 14(3), 2211-2215.

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