Stata se 14.0 for windows

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Stata/SE 14.0 for Windows is a powerful data analysis and statistical software package. It provides advanced data management, analysis, and visualization capabilities for researchers and professionals. The software is designed to handle large datasets and complex statistical models, making it a versatile tool for a wide range of applications.

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8 protocols using stata se 14.0 for windows

Prostate Cancer Circulating Tumor Cells

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The analysis was performed using the programme Stata (Stata/SE 14.0 for Windows, Stata Corp Lp, 20159, describing according to the nature and distribution of the quantitative and ordinate variables with measurements of central tendency (mean and median) and of dispersion using the interquartile range (IQR) and standard deviation (SD). The Shapiro-Wilk test was used to define the null hypothesis with respect to the normal distribution. The nominal dichotomous variables were described as proportions with their respective confidence intervals.
Age, total serum PSA, percentage of positive biopsy cores, the Gleason Score of prostate biopsy, the Gleason Score of the surgical specimen, pathological stage T2a or less, extracapsular extension, surgical margins, seminal vesicle and lymph node infiltration according to its statistical were compared to the absence or presence of primary CPCs.
Student's t-test and Mann-Whitney test was used to compare quantitative variables. Hypothesis testing to compare two population proportion and Fishers´ Exact tests were used to compare frequencies on nominal variables. A P-value of ≤0.05 was taken to signify statistical significance and all tests were two tailed.

Murray N.P., Reyes E., Fuentealba C., Aedo S, & Jacob O. (2017). The presence of primary circulating prostate cells is associated with upgrading and upstaging in patients eligible for active surveillance. ecancermedicalscience, 11, 711.

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Socio-demographic Predictors of Stigma and Illness Uncertainty

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All data were entered in Microsoft Excel 2013 and analyzed using the STATA SE 14.0 for Windows. Genderspecific estimates of means and proportions along with estimates of variability were determined for all socio-demographic and outcome variables. These variables were further compared using two-sample t test, the Wilcoxon rank-sum test, chi-squared test and analysis of variance as indicated. Pairwise Pearson's correlation coefficient was calculated between the two outcomes' mean scores.
Factor analysis with varimax rotation was done for both outcome scales. Items that had loadings greater than 0.4 were retained. Several models ranging from 2 to 5 factor solutions were examined and the most parsimonious model was determined based on: (1) eigenvalues >1; (2) total variance explained by the model and (3) intuitive meaningfulness of the factors described [40] . Mean subscale scores were calculated for each outcome. Cronbach's alpha internal reliability coefficients were calculated for all stigma and illness uncertainty scales and subscales.
Age and sex controlled multiple linear regression analyses were conducted for each outcome to determine predictive variables.

Blake A., Asnani V., Leger R.R., Harris J., Odesina V., Hemmings D.L., Morris D.A., Knight-Madden J., Wagner L, & Asnani M.R. (2018). Stigma and illness uncertainty: adding to the burden of sickle cell disease. Hematology (Amsterdam, Netherlands), 23(2).

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Antipsychotic Use and Natural Death

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Chi-square test and independent samples t-test were used for comparison between groups. The variables were dichotomized after exclusion of the “Don’t know” answers. Conditional logistic regression was used to calculate crude and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of the association between antipsychotic use and natural death compared with no antipsychotics use. Then, the same method was used to calculate crude and adjusted ORs and 95% CIs of the association between antipsychotic polypharmacy and natural death compared with antipsychotic monotherapy as it represented the recommended therapy regimen. A univariate analysis including all potential confounders was performed. A multivariable analysis was then performed including all variables with p values <0.10 in univariate analysis in the final model. Statistical significance was defined as a p-value <0.05. To investigate effect-measure modification, we stratified our analyses by gender and age. All analyses were performed using Stata/SE14.0 for Windows.

Chen Y., Yang X., Qin X., Yang Q., Fan H., Li J., Song X., Xu S., Guo W., Deng W., Wang Q., Li T, & Ma X. (2019). Antipsychotics and risk of natural death in patients with schizophrenia. Neuropsychiatric Disease and Treatment, 15, 1863-1871.

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Gestational Diabetes Risk Factors

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Data were presented as means and standard deviations for continuous variables, and as number and percentages for categorical variables. Student’s t-tests, Chi-squared tests and Fisher’s exact tests were used to identify the differences in clinical characteristics between the GDM and non-GDM groups. Linear regression were used to compare the difference in the clustering of risk factors between subjects with overweight/obesity and subjects with normal BMI. A logistic regression analysis was applied for the relationship between the number of risk factors and GDM, using GDM as the dependent variable. Logistic regression analyses were performed to identify important risk factors and to estimate their odds ratios of GDM. Interactions between risk factors and overweight/obesity on the risk of GDM were calculated. Statistical analyses were performed using Stata ⁄ SE 14.0 for Windows (StataCorp, College Station, TX, USA). The level of significance for all tests was p<0.05.

Yen I.W., Lee C.N., Lin M.W., Fan K.C., Wei J.N., Chen K.Y., Chen S.C., Tai Y.Y., Kuo C.H., Lin C.H., Hsu C.Y., Chuang L.M., Lin S.Y, & Li H.Y. (2019). Overweight and obesity are associated with clustering of metabolic risk factors in early pregnancy and the risk of GDM. PLoS ONE, 14(12), e0225978.

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Cytological Features of Thyroid Nodules

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A total of 22 quantified cytological features, including 16 morphological and 6 chromatic features, were computed and analyzed. Analysis of variance and the Scheffé test were used to compare the differences in cytological features among 4 types of thyroid nodules based on a pathologic diagnosis. The D’Agostino-Pearson test was used to test for normal distribution of each feature. Multivariate logistic regression analysis was used to investigate the relationship between cytological features and pathologic results. Statistical analysis was performed using MedCalc Version 17.6 (MedCalc Software, Mariakerke, Belgium) and Stata/SE 14.0 for Windows (StataCorp LP, TX, USA). A p value less than 0.05 was considered statistically significant.

Shih S.R., Jan I.S., Chen K.Y., Chuang W.Y., Wang C.Y., Hsiao Y.L., Chang T.C, & Chen A. (2019). Computerized Cytological Features for Papillary Thyroid Cancer Diagnosis—Preliminary Report. Cancers, 11(11), 1645.

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Early Childhood Caries Risk Factors

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Age was categorised into 6–11-months-old, 12–23-months-old, 23–35-months-old, 35–47-months old; 48–59-months-old and 60–71-months old. The mean dmft, dmfs, and pufa scores for each age group and each tooth type were computed. The prevalence of ECC was calculated as the proportion of participants with ICDAS-1(d^1–6) greater than zero. The percentage of children with ECC was determined according to two ICDAS II thresholds (ICDAS-2(d^1–2), and ICDAS-3(d^3–6)) for non-cavitated and cavitated carious lesions respectively. The differences in mean dmft, dmfs, pufa scores, and the percentages of children with ICDAS 1, 2, and 3 scores among age groups were computed using ANOVA and Chi test respectively.
The prevalence of each ECC risk indicator—frequency of tooth brushing, consumption of refined carbohydrate in-between-meals, daily use of fluoridated toothpaste, and dental service utilization in the 12 months preceding the study—was computed for each age group. The differences in the prevalence of the ECC risk indicators among age groups were also compared using the Chi test.
Linear regression analysis was done to identify risk indicators for the ECC SiC index. Statistical analyses were conducted with Stata/SE 14.0 for Windows. The significance level was set at p < 0.05.

Folayan M.O., Oginni A.B., El Tantawi M., Finlayson T.L, & Adeniyi A. (2021). Epidemiological profile of early childhood caries in a sub-urban population in Nigeria. BMC Oral Health, 21, 415.

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Meta-analysis of Birth Defect Risks

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The analysis was performed using Review Manager 5.3 software provided by the Cochrane network for meta-analysis. The ORs for birth defects in the infants conceived with ART and NP offspring in the cohort studies were combined, and their 95% CIs were calculated. Since the prevalence of birth defects was 10% in all studies, we assumed that the adjusted OR was equal to the adjusted relative risk (RR: Heisey^{[13 (link)]} 2015).^{[9 ,13 (link)]} The chi-squared test was used to determine the heterogeneity of the included studies. If P > .1 and I² < 50%, a study was considered to be homogeneous, and the fixed effects model (the Mantel–Haenszel method) was used for analysis. If P < .1 or I²< 50%, a study was not considered homogeneous, and we used subgroup analysis or sensitivity analysis to determine the cause of heterogeneity. Finally, we also tested the included studies for publication bias. If the number of included articles was less than 10, Egger’s regression asymmetry test was used to evaluate publication bias. Otherwise, Begg’s funnel plot and Egger’s test for asymmetry were used to evaluate publication bias. Publication bias was assessed using Stata/SE14.0 for Windows (Stata Corp LP, College Station) and RevMan5.3.

Lu Y., Liu L., Zhang P., Sun Y., Ma C, & Li Y. (2022). Risk of birth defects in children conceived with assisted reproductive technology: A meta-analysis. Medicine, 101(52), e32405.

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Oral Health Determinants in Children

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The normal distribution of the explanatory variables (ACE, bully victimization, self-esteem, resilience, social support) was determined. The mean (SD) and median (Interquartile range - IOR) of the scores for the explanatory variables were computed. The association between the categorized outcome variables (caries, complications of caries, and poor oral hygiene) and age, sex, socioeconomic status was assessed using chi square test or Mann Whitney U test. The associations with the explanatory variables (ACE, bully victimization, self-esteem, resilience and social support) were determined using the Mann Whitney U test and Kruskal-Wallis test for the variables that were skewed and the t test for those that were normally distributed. Univariate and multivariable logistic regression was conducted to determine the crude and adjusted odds ratios. The models to determine the risk indicators for poor oral hygiene, caries, and complications of caries were adjusted for age, sex and socioeconomic status, which are factors associated with caries, oral hygiene status of children and ACE [68 (link)–70 ]. Statistical significance was conducted with Stata/SE 14.0 for Windows (2015) and measured as p < 0.05.

Folayan M.O., Oginni O., Arowolo O, & El Tantawi M. (2020). Association between adverse childhood experiences, bullying, self-esteem, resilience, social support, caries and oral hygiene in children and adolescents in sub-urban Nigeria. BMC Oral Health, 20, 202.

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