univariate analysis

univariate analysis

techniques of multivariate analysis that can be used when analyzing variation in a data set in which there is only a single variable parameter of interest.

univariate analysis

(statistics) an analysis of a single character.
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All variables were included in univariate analysis but for multiple regression analysis only those variables were included that had p<0.25 and results were reported as crude and adjusted hazard ratios.
A univariate analysis showed that self-rated health as fair or poor and all SF-36 subscale scores, except for mental health and role emotional subscales, were predictors of mortality.
The researchers found that the rate of FS recurrence was significantly lower in the rectal acetaminophen versus the no antipyretic group (9.1 versus 23.5 percent; P < 0.001) in univariate analysis. Rectal acetaminophen use was the largest contributor to the prevention of FS recurrence during the same fever episode among the variables in the final multiple logistic regression analysis (odds ratio, 5.6; 95 percent confidence interval, 2.3 to 13.3).
the evaluation software of the mass spectrometer should allow univariate analysis of signal intensities of the image data and possibilities for the determination of standard deviations of the signal intensities, "receiver operating characteristic" curves (roc curves) have the execution of hypothesis tests.
The variables with P < 0.05 (showing evidence of association) in univariate analysis could be retested in multivariate analyses using a logistic regression model to select the potential factors influencing tumor responses to neoadjuvant chemoradiation, and odd ratios (OR) with 95% confidence intervals (CIs) were calculated.
Table 1 lists patient characteristics, other case details, and results of univariate analysis. The patients were 143 males and 52 females with median age of 49 years (range: 18 to 85 years).
For univariate analysis, Chi-square test or Fisher exact test was used to assess the relationship between the different subtypes and odd ratio with 95% confidence interval was computed.
Variables with a p value <0.05 in the univariate analysis were included into a multivariate logistic regression analysis.
Hence, with a correct multiple regression model, the estimate of the univariate analysis is based on a wrong model.
Univariate Analysis (Factors Affecting Successful Outcome) Variable p Value Age <50 years 0.025 Female gender 0.005 Nonsmoker 0.011 Not a current smoker 0.017 Not alcoholic 0.032 No h/o anti-TB treatment 0.033 No clubbing 0.009 Reticulonodular radiological pattern 0.005 No honeycombing in HRCT 0.003 Univariate analysis showed that patients aged <50 years, females, nonsmokers, and not current smokers, nonalcoholics with no past anti-TB treatment, no clubbing and with reticulonodular shadow and without honeycombing have successful outcome.