Statistical AnalysisStatistical ana

Statistical Analysis
Statistical analyses were performed using the SPSS software package (SPSS 13.0). Kolmogorov–Smirnov and Shapiro–Wilk tests were used to determine distribution of the data. Normally distributed data are expressed as mean±SD and were compared using the unpaired t test and 1-way ANOVA. Other data are expressed as median and range and were compared with nonparametric tests. χ2 and Fischer exact tests were used to determine associations between variables categorized. A value of P≤0.05 was considered statistically significant.
We performed 2 logistic regression models to investigate influences of clinical and neuroradiologic parameters on the end points: hematoma growth and long-term outcome after 1 year. Variables with a trend toward significance in univariate analysis (P≤0.1) were entered into stepwise forward inclusion multivariate logistic regression models for prediction of hematoma growth and outcome. In the multivariate regression analysis, a value of P≤0.05 was considered statistically significant.

Statistical Analysis
Statistical analyses were performed using the SPSS software package (SPSS 13.0). Kolmogorov–Smirnov and Shapiro–Wilk tests were used to determine distribution of the data. Normally distributed data are expressed as mean±SD and were compared using the unpaired t test and 1-way ANOVA. Other data are expressed as median and range and were compared with nonparametric tests. χ2 and Fischer exact tests were used to determine associations between variables categorized. A value of P≤0.05 was considered statistically significant. 
We performed 2 logistic regression models to investigate influences of clinical and neuroradiologic parameters on the end points: hematoma growth and long-term outcome after 1 year. Variables with a trend toward significance in univariate analysis (P≤0.1) were entered into stepwise forward inclusion multivariate logistic regression models for prediction of hematoma growth and outcome. In the multivariate regression analysis, a value of P≤0.05 was considered statistically significant.

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Statistical AnalysisStatistical analyses were performed using the SPSS software package (SPSS 13.0). Kolmogorov–Smirnov and Shapiro–Wilk tests were used to determine distribution of the data. Normally distributed data are expressed as mean±SD and were compared using the unpaired t test and 1-way ANOVA. Other data are expressed as median and range and were compared with nonparametric tests. χ2 and Fischer exact tests were used to determine associations between variables categorized. A value of P≤0.05 was considered statistically significant. We performed 2 logistic regression models to investigate influences of clinical and neuroradiologic parameters on the end points: hematoma growth and long-term outcome after 1 year. Variables with a trend toward significance in univariate analysis (P≤0.1) were entered into stepwise forward inclusion multivariate logistic regression models for prediction of hematoma growth and outcome. In the multivariate regression analysis, a value of P≤0.05 was considered statistically significant.

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Analisis Statistik
Analisis statistik dilakukan dengan menggunakan paket perangkat lunak SPSS (SPSS 13.0). Tes Kolmogorov-Smirnov dan Shapiro-Wilk digunakan untuk menentukan distribusi data. Data terdistribusi secara normal dinyatakan sebagai mean ± SD dan dibandingkan dengan menggunakan uji t berpasangan dan 1-way ANOVA. Data lain yang dinyatakan sebagai median dan jangkauan dan dibandingkan dengan tes nonparametrik. Tes yang tepat χ2 dan Fischer digunakan untuk menentukan hubungan antara variabel dikategorikan. Nilai dari P ≤ 0,05 dianggap signifikan secara statistik.
Kami melakukan 2 model regresi logistik untuk menyelidiki pengaruh parameter klinis dan neuroradiologic pada titik akhir: pertumbuhan hematoma dan hasil jangka panjang setelah 1 tahun. Variabel dengan kecenderungan penting dalam analisis univariat (P≤0.1) dimasukkan ke bertahap maju inklusi model regresi logistik multivariat untuk prediksi pertumbuhan hematoma dan hasil. Dalam analisis regresi multivariat, nilai P ≤ 0,05 dianggap signifikan secara statistik.

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