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University of Maryland School of Nursing: NRSG 795   Analysis #2: Comparing group means (10 points)   Background and objectives   A retirement home has undergone extensive environmental renovations focusing on fall prevention

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University of Maryland School of Nursing: NRSG 795

 

Analysis #2: Comparing group means (10 points)

 

Background and objectives

 

A retirement home has undergone extensive environmental renovations focusing on fall prevention. The next phase involves helping clients becoming more active to address balance and coordination, strength and aerobic capacity.  The mobilityintervention_F20.xlsx dataset represents data from two time points (baseline and 90 days later) of a fictitious study that explores the 90 day impact of two different interventions designed to help reduce clients’ think they have to totally rely on staff to help them get around. Clients completed several scales and then were randomly assigned to one of two exercise groups: strength exercises only or strength plus flexibility and balance.  Higher scores on the fear of falling and anxiety scales implies more fear and anxiety symptoms.  Higher scores on the confidence scale implies greater confidence in being able to walk unassisted.

 

The intent of this analysis is to have you use these data to demonstrate your ability to:

1)         Identify the appropriate statistical tests to test differences in means;

2)         Conduct analyses to test for statistical differences ( use either Excel or Intellectus Statistica (IS); and

3)         Summarize findings as you would in a journal article or report.

 

Assignment

Part 1: Describe the sample characteristics and baseline values, comparing the two groups’ characteristics.

 

With any analysis, the first step is to examine your data, assessing the degree of missing data, the potential miscodes, and conducting a descriptive analysis. Then, a table is created to describe the sample characteristics. Since this is an intervention study with two groups, the characteristics of the 2 groups should be described separately, rather than report on the entire sample. The example table shell below gives you an illustration of how this might look. Calculate the appropriate descriptive statistics for sex, age, the baseline anxiety, fear of falling and confidence scores. Then describe the findings in the table.

 

Table 1

Characteristics of clients at baseline (n=44)

 

		Strength only n=22		Strength plus n=22
		Mean	SD	Mean	SD
Age (years)
Baseline Values   Fear of falling
Confidence to walk unassisted
Anxiety
Gender		Frequency	%	Frequency	%
Female
Male

Note. Data source: mobilityintervention.xlsx.

 

Part 2:   Comparing two independent group means

 

In an intervention it is always good to examine if the groups are comparable at the start on the ‘thing’ that the intervention is targeting to change (in this case confidence to walk unassisted)

 

Follow the steps of hypothesis testing, stating the null hypothesis, review assumptions (show evidence you explored if the assumptions were met), and consider if the hypothesis is directional or not [HAVE TO DO BE IN YOUR PAPER] à ALL THESE STEPS MUST BE MENTIONED

Steps in Hypothesis Testing

1. State the null and alternative hypothesis, determine if directional and if using two-tailed or one-tailed test
2. Decide what test statistic to use
3. Make sure the data meet the necessary assumptions for the test statistic chosen
4. Establish the level of significance (usually 0.05)
5. Compute the test statistic
6. Compare test statistic to critical value- decide to accept or reject the null hypothesis
7. Obtain p-value- determine statistical significance
8. Clearly state the conclusion in words using the statistics as evidence not the finding in of themselves. (e.g., so you found significant differences in the means -well this alone doesn’t tell anyone anything. Instead describe what the results mean by writing it in words what test you used, which group had what value, how the means differed, etc.)

.  Consider if the distribution of the confidence score is approximately normal. You do not need to statistically test for homogeneity of variance in Excel but you should consider (calculate and ‘eye ball compare’)  if the standard deviations of the groups being compared are similar (hint: know how SD relates to variation) so you can select the proper t-test condition to run. Write a few sentences describing your steps and the results of the testing, making sure that you note what group means are being compared and what the results would mean to someone who does not understand statistics. This summary should be in YOUR OWN words and not copied from IS. Include a copy of your EXCEL output or if using SI a copy of the raw output view.

This video may be useful  http://www.youtube.com/watch?v=X14z9r8FUKY

See the end of the assignment for examples of how to write up the results.

 

Part 3:   Comparing means of a single group, pretest-posttest

 

After 90 days do we see early results that overall regardless of any group assignment that our interventions appear to be helping (i.e, reducing the fear of falling). For the entire sample (regardless of the intervention), test the hypothesis:

The fear of falling score will change over the 90 day period (i.e., compare Time 1 to Time 2).

 

Again, follow the steps of hypothesis testing, stating the null hypothesis, review assumptions, and consider if the hypothesis is directional or not. Make sure that you evaluate the assumptions for the statistical test, particularly the level of the measurement and the normality of the distribution. Write a few sentences describing your steps and the results of the testing, making sure that you note what group means are being compared and what the results would mean to someone who does not understand statistics. This summary should be in YOUR OWN words and not copied from IS. See the end of the assignment for examples of how to write up the results. Include a copy of your EXCEL output or if using SI a copy of the raw output view.

 

Part 4:  Comparing means of more than 2 groups

 

Feelings of anxiety may influence your success to reduce the fear of falling.  A variable has been created for you reflecting low, medium and high anxiety at baseline. Test the following hypothesis:

The fear of falling score at 90 days is statistically different for the three levels of baseline anxiety groups (low, medium, and high). **we’re comparing fear of falling between the three baseline groups**

 

As with the t-tests, assumptions of the statistical tests must be considered.  You do not need to test for homogeneity of variance in Excel but you should consider if the standard deviations of the 3 groups being compared are similar. Write a few sentences describing your steps and the results of the testing, making sure that you note what group means are being compared and what the results would mean to someone who does not understand statistics.  This summary should be in YOUR OWN words and not copied from IS.  Include a copy of your EXCEL output or if using SI a copy of the raw output view.  If the ANOVA F test is significant, further post hoc testing would be needed to compare which means are statistically different (e.g., Group 1 vs 2? Group 1 vs 3? Group 2 vs. 3?).  This video shows you how to do this in Excel http://www.youtube.com/watch?v=tPGPV_XPw-o  but it is not required for this assignment (you need to indicate to your instructor what software you are using).

See the end of the assignment for examples of how to write up the results.

 

 

 

**Extra Notes from tutoring for guidance**

There are certain assumptions that must be met for the results of a t-test to be valid. These assumptions are:

1. Participants have been randomly sampled (this is often violated).
2. Variables have the correct level of measurement. The dependent variable is measured at the interval or ratio level and the independent variable is nominal (group).
3. The dependent variable is normally distributed.

The mean, median and mode have to be written out and shown how they are similar and the same

The variances in the groups being compared are similar. This is called homogeneity of variance or homoscedasticity.

One way to get a rough estimate of whether population variances are equal is to compare the standard deviations between the two groups. If the variances are similar, then the standard deviations (i.e., square root of variance) should be similar.

There are two formulas to calculate independent t –tests and which one to use is determined on whether the variances of the groups being compared are equal (independent t test for pooled samples) or if the variances differ (independent t test for separate samples).

We are doing a paired t-test, write assumption, level of significance is 0.05,