Stata program version 10

Manufactured by StataCorp

Sourced in United States

STATA program version 10 is a statistical software package designed for data analysis, management, and presentation. It provides a wide range of tools for handling various types of data, including cross-sectional, time-series, and panel data. The program offers a comprehensive set of statistical methods, from basic descriptive statistics to advanced econometric techniques.

Automatically generated - may contain errors

Lab products found in correlation

Spelling variants of this product

Stata (4799 citations) Stata 10.0 (596 citations) STATA version 10 (440 citations) STATA program (29 citations) STATA 10 Program (2 citations) STATA versions (2 citations)

10 protocols using stata program version 10

Myelopathic Signs Determinants Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols

Descriptive statistics were used to analyze the participants’ characteristics and clinical myelopathic signs. Continuous variables were analyzed by the mean and standard deviation (SD). Categorical variables were considered in terms of frequency and percentage. Each variable was categorized into an ordinal scale for further logistic regression analysis.
Univariate logistic regression was used to determine the association between factors and a participant’s positive, at least one, clinical myelopathic sign. The variables that reached a p-value of less than 0.2 in the univariate logistic regression analysis were included in the multiple logistic regression model. The backward stepwise elimination process was applied for multivariate logistic regression analysis; variables with p-values of less than 0.05 were considered statistically significant. The data were analyzed using the STATA program version 10 (STATA, College Station, TX, USA).

Puntumetakul R., Chatprem T., Saiklang P., Phadungkit S., Kamruecha W, & Sae-Jung S. (2022). Prevalence and Associated Factors of Clinical Myelopathy Signs in Smartphone-Using University Students with Neck Pain. International Journal of Environmental Research and Public Health, 19(8), 4890.

+ Open protocol

+ Expand

Factors Associated with Vertebral Fractures

Check if the same lab product or an alternative is used in the 5 most similar protocols

Continuous parameters were reported as mean and standard deviations (SD). Categorical parameters were reported as numbers and percentages. Univariate and multivariate logistic regression analyses were used to determine the associations between clinical factors and vertebral fractures. All statistical analyses were performed by the STATA program version 10 (StataCorp, College Station, TX). Statistical significance was considered as a p value < 0.05.

Teawtrakul N., Chukanhom S., Charoensri S., Somboonporn C, & Pongchaiyakul C. (2020). The Trabecular Bone Score as a Predictor for Thalassemia-Induced Vertebral Fractures in Northeastern Thailand. Anemia, 2020, 4634709.

+ Open protocol

+ Expand

Lower Extremity Alignment Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols

Descriptive statistics were used to analyze characteristics of participants and lower extremity alignment variables. Continuous variables, including age, average working hours per day, and years working, were analyzed by mean and standard deviation (SD). Categorical variables, including sex, BMI, and lower extremity malalignment characteristics, were considered in terms of frequency and percentage. Simple logistic regression analysis was used to include each independent variable into a multiple logistic regression model. The variables with a P-value less than 0.2 were included in the multiple logistic regression model. Multiple logistic regression analysis was performed using a stepwise regression process. The variables with P-value less than 0.05 were considered to be statistically significant.33 Data were analyzed using the STATA program version 10 (STATA, College Station, TX, USA).

Karukunchit U., Puntumetakul R., Swangnetr M, & Boucaut R. (2015). Prevalence and risk factor analysis of lower extremity abnormal alignment characteristics among rice farmers. Patient preference and adherence, 9, 785-795.

+ Open protocol

+ Expand

Clinical Predictors of Bacterial Infection

Check if the same lab product or an alternative is used in the 5 most similar protocols

Continuous parameters were reported as the mean and standard deviation (SD). Categorical parameters were reported as the number and percentage. Clinical predictive factors for bacterial infection were analyzed by univariate and multivariate logistic regression methods. All statistical analyses were performed using STATA program version 10 (StataCorp, College Station, TX, USA). A probability value of less than 0.05 was considered statistically significant.

Teawtrakul N., Jetsrisuparb A., Sirijerachai C., Chansung K, & Wanitpongpun C. (2015). Severe bacterial infections in patients with non-transfusion-dependent thalassemia: prevalence and clinical risk factors. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 39.

+ Open protocol

+ Expand

Comparing Postoperative Analgesia Needs

Check if the same lab product or an alternative is used in the 5 most similar protocols

After accounting for a 20% dropout rate, software for statistics and data science (Stata program version 10; Stata Corp LLC, Texas, USA) revealed that 60 patients (30 per arm) were required (setting an alpha error of 5% and power of 90%). The percentage of patients who required extra analgesia (pentazocine) within 24 h after surgery was much lower in the T group (57%) than in the GA group8 (link) (94%).

Shokri H., Ali I, & Kasem A.A. (2021). Evaluation of the Analgesic Efficacy of Bilateral Ultrasound-Guided Transversus Thoracic Muscle Plane Block on Post-Sternotomy Pain: A Randomized Controlled Trial. Local and Regional Anesthesia, 14, 145-152.

+ Open protocol

+ Expand

Mental Health and Family Factors

Check if the same lab product or an alternative is used in the 5 most similar protocols

To determine the association between the severity and type of mental problems and family background issues, the crude odds ratios and 95% confidence intervals (95% CI) were computed by bivariate logistic regression. We performed multivariate logistic regression to obtain an adjusted odds ratio and the 95% confidence interval. On multivariate analysis, we controlled for the effects of confounding variables, which were selected using the following criteria: (i) variables which were found to have a p-value less than 0.25 in crude analysis and ii) variables shown from previous reports to have effects on mental problems. The model fitting procedure was backward stepwise elimination.
All analyses were performed using the Stata program version 10 (Lakeway, TX, USA). All tests were two-sided and a p value < 0.05 was considered statistically significant.

Luvira V., Nonjui P., Butsathon N., Deenok P, & Aunruean W. (2023). Family Background Issues as Predictors of Mental Health Problems for University Students. Healthcare, 11(3), 316.

+ Open protocol

+ Expand

Osteoporosis Risk Factors Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols

Continuous results are presented as mean and standard deviations (SD). Categorical results are reported as numbers and percentages. Logistic regression analyses were used to investigate the relationship between variables and osteoporosis with a signi cance level of P < 0.05. The receiver-operating characteristics (ROC) curve was used to determine the area under the ROC curve and de ne the optimal cut-off point. The sensitivity and speci city were calculated using a 2x2 table. The STATA program version 10 was used for all statistical analyses (StataCorp, College Station, TX).

Teawtrakul N., Chansai S., Yamsri S., Chansung K., Wanitpongpun C., Lanamtieng T., Phiphitaporn P., Fucharoen S, & Pongchaiyakul C. (2023). The association of growth differentiation factor-15 levels and osteoporosis in patients with thalassemia. The American journal of the medical sciences, 366(2).

+ Open protocol

+ Expand

Smartphone Usage and Musculoskeletal Disorders

Check if the same lab product or an alternative is used in the 5 most similar protocols

Descriptive statistics were used to analyze characteristics of participants and musculoskeletal disorder variables. Continuous variables, including age, weight, height, study hours per day, years of smartphone usage, average smartphone usage hours per occurrence/day/year, years of using other devices, average usage of other devices in hours per occurrence/day/year, were analyzed by mean and standard deviation (SD). Categorical variables, including sex, BMI, hand dominance, smoking behavior, drinking behavior, exercise behavior, underlying disease, underlying musculoskeletal disease, accident history, the use of smartphones data, stress level, musculoskeletal disorders and level and ergonomic risks were considered in terms of frequency and percentage. The Chi-Square test and Fisher's exact test were used to quantify the relationship between the musculoskeletal disorders and the ergonomic risk among smartphone users. The variables with p-value less than 0.05 were considered statistically significant. Data were analyzed using the STATA program version 10 (STATA, College Station, TX, USA).

Namwongsa S., Puntumetakul R., Neubert M.S., Chaiklieng S, & Boucaut R. (2018). Ergonomic risk assessment of smartphone users using the Rapid Upper Limb Assessment (RULA) tool. PLoS ONE, 13(8), e0203394.

+ Open protocol

+ Expand

Factors Associated with Alloantibodies

Check if the same lab product or an alternative is used in the 5 most similar protocols

All statistical analysis was performed using the STATA program version 10 (StataCorp, College Station, TX). Categorical variables were reported as frequency and percentage. Continuous variables were presented as mean ± standard deviation (SD). Logistic regression analysis was used to identify factors associated with alloantibodies. A p-value <0.05 was considered statistically significant.

Teawtrakul N., Songdej D., Hantaweepant C., Tantiworawit A., Lauhasurayotin S., Torcharus K., Sripornsawan P., Sutcharitchan P., Surapolchai P., Komvilaisak P., Saengboon S., Pongtanakul B, & Charoenkwan P. (2022). Red blood cell alloimmunization and other transfusion-related complications in patients with transfusion-dependent thalassemia: a multi-center study in Thailand. Transfusion, 62(10), 2039-2047.

+ Open protocol

+ Expand

Smartphone Usage and Musculoskeletal Disorders

Check if the same lab product or an alternative is used in the 5 most similar protocols

Descriptive statistics were used to analyze characteristics of participants and musculoskeletal disorder variables. Continuous variables were analyzed by mean and Standard Deviation (SD). The continuous variables included age, weight, height, study hours per day, years using smartphone, average hours using smartphone at a time and per day, years using other electronic devices, average time using other devices at a time and per day. Categorical variables were considered in terms of frequency and percentage. Categorical variables included: gender, Body Mass Index (BMI), hand dominance, smoking behavior, alcohol drinking behavior, exercise behavior, underlying disease, underlying musculoskeletal disorders, accident history, characteristics of smartphones used (namely model, brand etc.), stress, and musculoskeletal disorders. Simple logistic regression analysis was used to include each independent variable into a multiple logistic regression model; variables with a p-value less than 0.2 were included in the multiple logistic regression model. Multiple logistic regression analysis was performed using a stepwise regression process; variables with p-values of less than 0.05 were considered to be statistically significant. Data were analyzed using the STATA program version 10 (STATA, College Station, TX, USA).

Namwongsa S., Puntumetakul R., Neubert M.S, & Boucaut R. (2018). Factors associated with neck disorders among university student smartphone users. Work (Reading, Mass.), 61(3).

+ Open protocol

+ Expand

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Revolutionizing how scientists
search and build protocols!