For item revision, the items were analyzed using IRT and the reliability and validity of the revised test instrument was analyzed. BILOG-MG ver. 3.0 (Scientific Software International Inc., Skokie, IL, USA) and IBM SPSS ver. 19.0 (IBM Co., Armonk, NY, USA) were used for item analysis. Internal reliability using Cronbach’s α coefficient and test-retests were conducted to assess the reliability of the revised CCTS, and the correlations between scores at two time points were measured using Pearson correlation coefficients. The content validity of the revised items was calculated as a percentage of the degree of agreement between the intention of the instrument developers in item development and the judgments of six experts. The validity of the response process was analyzed using the content of qualitative data obtained through cognitive interviews on the respondents’ response processes. Construct validity was tested using confirmatory factor analyses, which were conducted using the robust weighted least squares method known to be suitable for binary data [6 (link)]. Mplus ver. 6.11 (Muthen & Muthen, Los Angeles, CA, USA) and IBM SPSS ver. 19.0 (IBM Co.) were used to verify the goodness of the tests.
Spss ver 19
Manufactured by IBM
Sourced in United States
SPSS version 19.0 is a statistical analysis software package developed by IBM. It provides tools for data management, analysis, and presentation. The software is designed to handle a wide range of data types and offers a variety of statistical techniques, including regression analysis, factor analysis, and hypothesis testing.
Automatically generated - may contain errors
Lab products found in correlation
Prism 5, by GraphPad (3 mentions)
Prism ver 5, by GraphPad (2 mentions)
Origin 9, by OriginLab (1 mentions)
Ver 14, by MedCalc (1 mentions)
Origin 8, by OriginLab (1 mentions)
Sas 9, by SAS Institute (1 mentions)
Spss statistics for windows version 19, by IBM (1 mentions)
Origin 2019b, by OriginLab (1 mentions)
R statistical software, by R Project for Statistical Computing (1 mentions)
Version 12, by MedCalc (1 mentions)
Sas ver 9, by SAS Institute (1 mentions)
Prism software, by GraphPad (1 mentions)
395 protocols using spss ver 19
1
Reliability and Validity Assessment of Revised CCTS
2
Multivariate Analysis of Lycoris Hybrid Traits
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Based on the materials in Table 1 , 5 vegetative characters (leaf length, leaf width, bulb diameter, bulb weight, and leaf twist angle) and 5 propagule characters (tepal length, floral tube length, filament length, symmetry degree of flower, and undulate degree of tepal) of the species were used as units (artificial hybridization of Lycoris × jinzheniae is listed separately). SPSS ver. 19.0 was used to standardize and extract the principal components and test the cumulative contribution rate of the first two principal components. Then, the devtools and ggbiplot software packages of R v3.6.0 were used. Principal component analysis was performed on all traits, vegetative traits, and propagule traits [37 (link)].
Three vegetative characters (leaf length, leaf width, and bulb diameter) and three propagule characters (tepal length, floral tube length, and filament length) were selected, and SPSS ver. 19.0 was used to make boxplots to compare morphological differences and test for significance [10 (link)].
Three vegetative characters (leaf length, leaf width, and bulb diameter) and three propagule characters (tepal length, floral tube length, and filament length) were selected, and SPSS ver. 19.0 was used to make boxplots to compare morphological differences and test for significance [10 (link)].
3
Proteomic Analysis of Metal Stress
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SPSS ver. 19.0 was used to perform parametric one-way analysis of variance (ANOVA) for analyzing the differences in the growth rate, Fv/Fm, Y(II), and rETR values of the cultures among different groups.
Differentially expressed proteins were filtered using a fold change ≥ 1.2 and ≤0.83, and P-value < 0.05 (paired t-test or one-way ANOVA) (Cox and Mann, 2008 (link)). Blast2GO ver. 5.2 (BioBam, Spain) was used to annotate Gene Ontology (GO) function entries for all identified proteins, and Kyoto Encyclopedia of Genes and Genomes (KEGG) Automatic Annotation Server (KAAS) was used to allocate the differentially expressed proteins to the biological pathways. GO function and each KEGG pathway protein were analyzed for the significance of enrichment using Fisher’s exact test.
The paired t-tests were performed on the corrected ratios (the intensity of the fragmented tag in a sample to the intensity of the fragmented tag in the control sample) to identify the proteins and their proteomic associations after Fe or Cu deductions. The Cochran–Mantel–Haenszel tests for repeated 2 × 2 tests of independence were performed to identify the proteins under the conditional association of copper and iron (Rayner and Rippon, 2018 (link)). All tests were performed and verified using SPSS ver. 19.0.
Differentially expressed proteins were filtered using a fold change ≥ 1.2 and ≤0.83, and P-value < 0.05 (paired t-test or one-way ANOVA) (Cox and Mann, 2008 (link)). Blast2GO ver. 5.2 (BioBam, Spain) was used to annotate Gene Ontology (GO) function entries for all identified proteins, and Kyoto Encyclopedia of Genes and Genomes (KEGG) Automatic Annotation Server (KAAS) was used to allocate the differentially expressed proteins to the biological pathways. GO function and each KEGG pathway protein were analyzed for the significance of enrichment using Fisher’s exact test.
The paired t-tests were performed on the corrected ratios (the intensity of the fragmented tag in a sample to the intensity of the fragmented tag in the control sample) to identify the proteins and their proteomic associations after Fe or Cu deductions. The Cochran–Mantel–Haenszel tests for repeated 2 × 2 tests of independence were performed to identify the proteins under the conditional association of copper and iron (Rayner and Rippon, 2018 (link)). All tests were performed and verified using SPSS ver. 19.0.
4
Statistical Analysis of Pain Symptoms
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IBM SPSS ver. 19.0 (IBM Co., Armonk, NY, USA) was used for statistical analyses, and significance was indicated by p < 0.05. The chi-squared test, Mann–Whitney U test, and Wilcoxon signed-rank test were used to determine the inter- and intra-group statistical differences. The correlations among age, number of injections, symptom duration, and baseline VAS score were analyzed using linear regression.
5
Statistical Analysis in Biomedical Research
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Statistical analyses were performed using IBM SPSS ver. 19.0 (SPSS Inc., Chicago, IL, USA). All of the values were based on two-sided statistical analysis, and a p-value of <0.05 was determined to indicate a statistically significant difference.
6
Analyzing Diabetes and Lumbar Spine Severity
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We performed statistical analysis using IBM SPSS ver. 19.0 (IBM Corp., Armonk, NY, USA). All data are presented as mean±standard deviation or percentages. Clinical characteristics were compared between the groups using linear model analysis for continuous variables and the chi-square test for categorical data. Multinomial logistic regression analysis was adopted to identify the relationship between DM and the severity of LCS.
7
Comparative Analysis of Surgical Outcomes
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Continuous data were presented as mean ± standard deviation, and categorical variables were presented as number (%). The two surgical groups were compared in terms of BVCA, endothelial cell count (ECC), spherical equivalent, and astigmatism using the paired t-test. All statistical analyses were performed using IBM SPSS ver. 19.0 (IBM Co., Armonk, NY, USA). A p-value less than 0.05 was considered to indicate statistical significance.
8
Analyzing Patent-Publication Correlation
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Evidence suggests that a high correlation between patents and publications during periods of growth is indicative of substantial innovation [11 ]; therefore, correlation coefficients were calculated. In the case of a monotonic relationship, Pearson's or Spearman's rank was used for linear or non-linear associations, respectively. The coefficient of determination (R2) was used to quantify and compare the fit of data to linear and exponential trend lines. Statistical analysis was performed using the IBM SPSS ver. 19.0 (IBM Co., Armonk, NY, USA).
9
Predictors of Urinary Incontinence Recovery
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Univariate analysis was performed using the Student t-test for continuous variables and the chi-square test for categorical variables at 1, 3, 6, and 12 months after surgery. Multivariate logistic regression analysis was used to confirm independent predictive factors for urinary incontinence. According to the time of pad use, the Cox proportional hazard model was used to identify predictors of recovery from urinary incontinence. In addition, cut-off values for independent factors of urinary incontinence on cystography parameters were determined using receiver operating characteristic (ROC) curves. All analyses were performed using IBM SPSS ver. 19.0 (IBM Corp. Armonk, NY, USA). Statistical significance was set at p<0.05.
10
Triplicate Cell Proliferation Assay
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All experiments were repeated three times, and each experiment was performed in four parallel wells. All data were analyzed using SPSS ver.19.0 (IBM, Armonk, NY, USA) and expressed as mean ± standard deviation (SD). One-way analysis of variance (ANOVA) and Dunn’s multiple comparison test were used to analyze statistical differences. When P < 0.05, the difference was considered statistically significant.
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