Sentences with phrase «way analysis of variance»

The research design employed a one - way analysis of variance to determine if securely attached persons reported greater satisfaction with their evangelical church participation than those who reported preoccupied, dismissing, or fearful attachment.

In order to answer the hypothesis about the influence of education, income, and relationship status on the adult attachment style (H2 and H3), a three - way analysis of variance was implemented.

The choice of multiple t - tests for analysis of the outcome data is considered appropriate, although a simple two - way analysis of variance would have been a better choice and could have examined simultaneously the effects of the treatments on outcome measures and the differences between pre - and post-treatment measurements.

A one - way analysis of variance indicated significant mean differences in egalitarianism between groups on the DTAS (p <.0001).

Main and interaction effects of gender, ETLE, and MAOA genotype on the physical aggression score were calculated by using three - way analysis of variance (ANOVA).

We used one - way analysis of variance or independent sample t - tests to compare group differences on the measures of the continuous variables.

Doses of drugs over the trial were converted to mean daily equivalents of chlorpromazine and compared across groups by means of Kruskal - Wallis one way analysis of variance; this indicated no significant differences between treatment groups (medians of daily drugs in chlorpromazine equivalents: cognitive behaviour therapy 425, supportive counselling 517.75, routine care 450; χ = 0.963; P = 3D0.62).

Continuous variables were tested with one - way analysis of variance (ANOVA).

In bivariate analyses, we used 2 - way analysis of variance and χ2 tests of association to examine relationships between exposures, outcomes, and potential confounders.

To describe the obtained data, frequency table, mean and standard deviation were applied and for analyzing the data, independent t - test and one - way analysis of variance were used.

In Step 1, we conducted one - way analysis of variance (ANOVA) to determine whether there were site differences on the predictor and criterion variables.

We used a 2 - way analysis of variance (ANOVA) and Tukey honestly significant difference (HSD) tests to determine the effects of sex and reproductive status (treatment = intact versus sterilized) on the areas of the home ranges occupied by our study animals during the breeding and nonbreeding seasons.

A 2 - way analysis of variance (ANOVA) with repeated measures (time) was performed on all dependent variables recorded in the precondition and postcondition tests (SPSS).

A 2 - way analysis of variance (condition × time) with repeated measures was performed on all dependent variables recorded in the precondition and postcondition tests.

* P < 0.05, one - way analysis of variance (ANOVA) followed by Tukey's post hoc test.

A one - way analysis of variance (ANOVA) was used to assess variations in the time spent by fish in the focal region or in each compartment of the focal region (front, B1, B2, B3, and B4 for the Top view and top, middle, and bottom for the Side view, respectively) among the experimental conditions.

For continuous variables that were normally distributed, we used Student's t test or the one - way analysis of variance.

Statistical analysis of One - way Analysis of Variance (ANOVA) and Two - way Analysis of Variance (ANOVA) was carried out for comparing two data groups using GraphPad Prism 6 software for all experiments conducted in duplicates.

For variables with normal distribution, one way analysis of variance was used to compare mean values.

One - way analysis of variance was used to compare the mean number of nutrients that were correctly identified for different labelling systems (continuous data), followed by Scheffe post hoc testing.

One - way analyses of variance were used to test for significant overall mean differences by weight category groupings.

A chi - square test for group differences according to sex and one - way analyses of variance (ANOVAs) were used to examine differences in demographic variables using SPSS 18.0 for Windows.

To evaluate the associations among DADS scores and measures of marital and family functioning, several one - way analyses of variance (ANOVA) were performed using procedures parallel to those described above.

For the descriptive analysis of the individuals with a different relationship status and to answer the first hypothesis, χ2 - tests for independent samples and one - way analyses of variance were used.

Not exact matches

Analysis of the temperature record can be attempted in a way that tries to attribute the variance to signals as opposed to noise.

Furthermore, the analyses showed that job satisfaction, social support, and ways of coping explain between 24 % and 38 % of the variance in subscales of marital satisfaction.

In the three - way - analysis of variance with partnership, age, and education as factors and the AAS depend as continuous dependent variable (N = 1675), three small but relevant significant main effects of partnership, F (1, 1663) = 24.41, p < 0.001, η2 = 0.01, age, F (2, 1663) = 8.56, p < 0.001, η2 = 0.01, and education, F (1, 1663) = 11.92, p < 0.001, η2 = 0.01 were observed.