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Spss software package v24

Manufactured by IBM
Sourced in United States

SPSS software package v24.0 is a comprehensive statistical software tool developed by IBM. It offers a wide range of statistical analysis capabilities, including data management, analysis, and reporting. The software is designed to help users explore data, identify patterns, and make informed decisions based on statistical insights.

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Lab products found in correlation

4 protocols using spss software package v24

1

Cognitive and Audiometric Outcomes in Cochlear Implantation

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To compare cognition (RBANS-H), audiometric data and self-reported outcomes (NICQ, GBI, HISQUI19, SSQ12, HADS) between the age groups (< 60y and ≥ 60y) at two time points (before and after implantation), the t-test (when the data were normally distributed) or the Mann–Whitney U test were used. To measure the difference within the groups, the t-test (when the data were normally distributed) or the Wilcoxon test were used. Normality was assessed by the Kolmogorov–Smirnov test and Q-Q plots.
Pearson’s correlation coefficient was independently calculated for the < 60y and the ≥ 60y group to evaluate the relationship between cognition (RBANS-H), age, audiometric data (PTA4 and speech perception test results), and the questionnaire scores (NICQ, GBI, HISQUI19, SSQ12, HADS). Analysis of variance (ANOVA) was used to measure the association between gender and cognition.
Missing data and the response option “Not applicable” were treated as missing values. A level of p ≤ 0.05 (2-tailed) was considered significant. Statistical analyses were done in the SPSS software package v24.0 (IBM Corp., Armonk, NY, USA).
Demographic characteristics and outcome measures are presented as absolute values, percentages and, where appropriate, the mean and ± SD are provided.
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2

Cognitive Functioning and Psychological Factors

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Demographic characteristics and outcome measures are presented as absolute values, percentages and, where appropriate, the mean and ±SD are provided.
Pearson’s correlation coefficient was calculated to evaluate the relationship between cognition (RBANS-H), demographic data (age and years of formal education), audiometric data (PTA4 and SDS), and the corresponding subscales of DS14 and HADS questionnaire scores.
Analysis of variance (ANOVA) was used to measure the association between cognition and sex, smoking, alcohol intake, physical activity, hypertension, diabetes, traumatic brain injury, and obesity.
Missing data and the response option “Not applicable” were treated as missing values. A level of p ≤ 0.05 (2-tailed) was considered significant. Statistical analysis was performed with the SPSS software package v24.0 (IBM Corp., Armonk, NY, United States).
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3

Hearing Implant Outcomes Evaluation

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Demographic characteristics and outcome measures are shown as absolute (n) and relative frequencies (%) and, if appropriate, as mean plus standard deviation (± SD) and range.
The Mann-Whitney U-test and unpaired t-test (when the data are normally distributed; normal distribution was assessed by the Kolmogorov-Smirnov test and Q-Q plots) were used to examine the difference between both groups' objective and subjective measures, and to explore if any difference was found in terms of type of surgery in the MD group. Use of hearing aid in the ear to be implanted was compared between the MD group and control group with the chi-squared test.
Correlation analysis using Pearson's coefficient or Kendall's tau (normally or non-normally distributed data, respectively) was performed to evaluate the relationship between the patients' scores on the questionnaires, audiometric data, speech perception test results, and age at implantation.
Missing data and the response option “not applicable” were treated as missing values. A level of p ≤ 0.05 (two-tailed) was considered significant. Statistical analyses were processed in the SPSS software package v24.0 (IBM Corp., Armonk, NY, USA).
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4

Meludia Program Efficacy Analysis

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Demographic characteristics and outcome measures are shown as absolute numbers (n) and relative frequencies (%), and if appropriate with mean ± standard deviation (SD) and range. Each Meludia level was scored as either complete or incomplete. The mean (± SD) was also calculated.
The data were normally distributed according to the Kolmogorov–Smirnov test. Intergroup (CI and NH) and intragroup (pediatric and adult populations) comparisons were made via Student’s T-test. The Chi-Square was used to compare the numbers of participants who completed the levels of each Meludia category.
Pearson’s correlation coefficient was calculated to assess the relationship between mean score of the different categories of Meludia program, and the corresponding subscales of the MuRQoL and the MuQPP.
A p value of ≤ 0.05 (2-tailed) was considered significant. Statistical analyses were conducted with the SPSS software package v24.0 (IBM, Armonk, NY, USA).
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