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Table 1.

Demographic characteristics of the sample.

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Table 1 Expand

Table 2.

Correlation matrix between abdominal inspiratory expansion and clinical and respiratory variables at baseline (N = 50). Pearson’s correlation coefficients (r) are shown. Statistically significant correlations (p < 0.05) are highlighted in bold.

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Table 2 Expand

Table 3.

Correlation matrix between abdominal inspiratory expansion and clinical and respiratory variables at baseline (N = 50). Pearson’s correlation coefficients (r) are shown. Statistically significant correlations (p < 0.05) are highlighted in bold.

More »

Table 3 Expand

Table 4.

Correlation matrix between abdominal inspiratory expansion and clinical and respiratory variables at baseline (N = 50). Pearson’s correlation coefficients (r) are shown. Statistically significant correlations (p < 0.05) are highlighted in bold.

More »

Table 4 Expand

Table 5.

Correlation matrix between abdominal inspiratory expansion and clinical and respiratory variables at baseline (N = 50). Pearson’s correlation coefficients (r) are shown. Statistically significant correlations (p < 0.05) are highlighted in bold.

More »

Table 5 Expand

Table 6.

Correlation matrix between abdominal inspiratory expansion and clinical and respiratory variables at baseline (N = 50). Pearson’s correlation coefficients (r) are shown. Statistically significant correlations (p < 0.05) are highlighted in bold.

More »

Table 6 Expand

Table 7.

Multiple linear regression model predicting abdominal inspiratory expansion. Dependent variable: abdominal inspiratory expansion (cm). Values represent unstandardized coefficients (B), standard errors (SE), standardized coefficients (β), 95% confidence intervals (CI), t values and p values.

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Table 7 Expand

Fig 1.

Histogram of standardized residuals from the multiple linear regression model.

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Fig 1 Expand

Fig 2.

Normal P–P plot of standardized residuals for the multiple regression model.

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Fig 2 Expand