Halal food in fontainebleau
thinking of doing a day trip there. any halal recommendations? i’m finding it hard to find anything online
u/shouldnotbethere — 13 days ago
u/shouldnotbethere
▲ 10 r/biostatistics
hi guys. im a medical student who is figuring her way out through doing medical research. the school and country I'm in doesn't really prioritize medical research, especially early on in medical school, so I've been trying to figure it out on my own using online resources and AI.
I've found myself stuck on the section of multivariate analysis for a study I'm doing. It's a retrospective cohort study that assesses factors impacting outcomes of neonatal surgical conditions. im doing analysis using SPSS.
I've been using AI to help me understand the SPSS output tables because this is my first time doing this, and it flagged my regression table saying there was major issues there. it recommended I put my systems of disease, gestational age and weight groups into less categories. I'm really confused now. Any insight would be appreciated from someone who actually knows what they're looking at (unlike me)
the following is my text in my paper and the SPSS table:
Multivariable Analysis
Binary logistic regression showed gestational age (COR: 1.18, 95% CI:1.08-1.28, p < 0.001), duration of admission (COR: 1.03, 95% CI: 1.00-1.06, p = 0.034), birth weight (COR = 1.91, 95% CI = 1.31-2.78, p = 0.001) and system of disease (p < 0.001) were significant predictors of outcomes. However, gender (p = 0.967), age at admission (p = 0.389), mode of delivery (p = 0.548), and indoor/outdoor (p = 0.969) were not significantly associated with the outcome.
In multivariable logistic regression adjusting for gender, age at admission, gestational age, mode of delivery, birth weight, indoor/outdoor status, duration of admission, and system of disease, gestational age emerged as a significant predictor of outcome (p = 0.037). For each additional week of gestational age, the odds of a patient surviving increased by 12% (Adjusted Odds Ratio [AOR]: 1.12, 95% CI: 1.01-1.24). System of disease was also significantly associated (p < 0.001). Among the systems studied, Gastrointestinal (AOR: 0.12, 95% CI: 0.01-1.00, p = 0.05) conditions demonstrated the lowest odds of survival compared to other systems. Neurological conditions (AOR: 0.15, 95% CI: 0.01-1.52, p = 0.227) showed trends towards lower odds of survival, although it did not reach statistical significance. Conversely, respiratory conditions (AOR: 0.03, 95% CI: 0.00-0.32, p = 0.003) showed the strongest negative association with survival.
Birth weight was no longer significant, but showed a borderline association with the outcome (p = 0.064), suggesting a 54% increase in the odds of survival for each unit increase in birth weight (AOR: 1.54, 95% CI: 0.98-2.43). Age at admission (p = 0.580), duration of admission (p = 0.068), gender (p = 0.779), mode of delivery (p = 0.724), and indoor/outdoor status (p = 0.980) did not exhibit statistically significant associations with the outcome. The logistic regression model demonstrated a modest fit to the data (Nagelkerke R Square = 0.21) and correctly predicted the outcome in 70.6% of cases.
u/shouldnotbethere — 17 days ago
hi guys. im a medical student who is figuring her way out through doing medical research. the school and country I'm in doesn't really prioritize medical research, especially early on in medical school, so I've been trying to figure it out on my own using online resources and AI.
I've found myself stuck on the section of multivariate analysis for a study I'm doing. It's a retrospective cohort study that assesses factors impacting outcomes of neonatal surgical conditions. im doing analysis using SPSS.
I've been using AI to help me understand the SPSS output tables because this is my first time doing this, and it flagged my regression table saying there was major issues there. it recommended I put my systems of disease, gestational age and weight groups into less categories. I'm really confused now. Any insight would be appreciated from someone who actually knows what they're looking at (unlike me)
the following is my text in my paper and the SPSS table:
Multivariable Analysis
Binary logistic regression showed gestational age (COR: 1.18, 95% CI:1.08-1.28, p < 0.001), duration of admission (COR: 1.03, 95% CI: 1.00-1.06, p = 0.034), birth weight (COR = 1.91, 95% CI = 1.31-2.78, p = 0.001) and system of disease (p < 0.001) were significant predictors of outcomes. However, gender (p = 0.967), age at admission (p = 0.389), mode of delivery (p = 0.548), and indoor/outdoor (p = 0.969) were not significantly associated with the outcome.
In multivariable logistic regression adjusting for gender, age at admission, gestational age, mode of delivery, birth weight, indoor/outdoor status, duration of admission, and system of disease, gestational age emerged as a significant predictor of outcome (p = 0.037). For each additional week of gestational age, the odds of a patient surviving increased by 12% (Adjusted Odds Ratio [AOR]: 1.12, 95% CI: 1.01-1.24). System of disease was also significantly associated (p < 0.001). Among the systems studied, Gastrointestinal (AOR: 0.12, 95% CI: 0.01-1.00, p = 0.05) conditions demonstrated the lowest odds of survival compared to other systems. Neurological conditions (AOR: 0.15, 95% CI: 0.01-1.52, p = 0.227) showed trends towards lower odds of survival, although it did not reach statistical significance. Conversely, respiratory conditions (AOR: 0.03, 95% CI: 0.00-0.32, p = 0.003) showed the strongest negative association with survival.
Birth weight was no longer significant, but showed a borderline association with the outcome (p = 0.064), suggesting a 54% increase in the odds of survival for each unit increase in birth weight (AOR: 1.54, 95% CI: 0.98-2.43). Age at admission (p = 0.580), duration of admission (p = 0.068), gender (p = 0.779), mode of delivery (p = 0.724), and indoor/outdoor status (p = 0.980) did not exhibit statistically significant associations with the outcome. The logistic regression model demonstrated a modest fit to the data (Nagelkerke R Square = 0.21) and correctly predicted the outcome in 70.6% of cases.
u/shouldnotbethere — 17 days ago