Class 10 Jeff Driskell, MSW, PhD Research for Social Workers Salem State University School of Social Work Class 10 Jeff Driskell, MSW, PhD

Today’s Class Announcements/Check-in Lecture Work time Data Analysis Frequencies Descriptive Statistics Measures of central tendency Work time

Reflection- Class 10 Article Reflection What are the indicators that lead you to believe your article is qualitative in nature (other than it saying so)? What type of method selected (i.e. grounded theory) Hypothetically the study you are proposing is qualitative in nature. Identify three types of rigor you would employ to increase trustworthiness.

Statistics and Interpretation  Statistics and Interpretation

Statistics Holistic Approach- It provides tools for- collection, analysis, interpretation/ explanation, and presentation of data. It provides tools for- description, prediction, and relationship identification Levels- What are the levels at which analysis are conducted? Univariate- Statistics that describe one variable at a time Bivariate- Statistics that looks at the relationship between two variables. Multivariate- Statistics that looks at the relationship between multiple variables

Ways to Organize and Present Data Tables Descriptive tables Frequency tables Graphs Bar Histogram Narrative Matrix Correlation

Statistical Analysis- What you need to know Purpose of test Match question to test Logistics for test Structure of variable needed for test Continuous Nominal Number of variables needed for test Interpret test findings Basic knowledge of the “squigglies” in reporting statistical results

Review: Variable structure Provide an example of a continuous level variable Provide an example of a discrete level variable

Types and Categories of Statistical Tests

4 basic categories of statistical tests Mean, standard deviation Median, Mode Percentage, frequency Description Pearson’s correlation Correlation Student’s t tests Chi-square tests ANOVA Odds ratios Comparison OLS regression Logistic regression Prediction

Statistical Tests: Implications of Normal Distributions Two categories of statistical tests 1. Parametric Used for normally distributed data Example- T-test, ANOVA Correlation Coefficient 2. Non-parametric Used for non-normally distributed data Mann-Whitney Wilcoxon’s matched tests Chi Square Kendall Spearman R

If You Want to Describe or Summarize Variables…

Univariate & Descriptive Univariate - describe individual variables Descriptive – describe, summarize data Frequency Range Percentage Central tendency (simple mean, median mode) Standard deviation

Frequencies A Frequency (f) is a count of the number of cases or characteristics of selected cases, i.e. the number of treatment sessions attended.

Frequency Distributions Two ways to display Frequency Distributions 1. Frequency tables 2. Histograms/Bar charts/Pie Graphs

Where do the Numbers Come From? Frequency Output in SPSS

Example- Frequency Table Frequency Distribution: Number of Children Reported by Parenting Class Participants Number of Children Frequency (f) 1 11 2 3 4 5 6 Total= 35

Example- Bar Graph

Histogram

Descriptive

Descriptive Statistics Statistical procedures used to summarise, organize, and simplify data. Raw data is made more manageable Raw data is presented in a logical form Patterns can be seen from organized data Frequency tables Graphical techniques Measures of Central Tendency Measures of Spread (variability)

Measures of Central Tendency A way of summarising the data using a single value that is in some way is representative of the entire data set. Three options… 1. Mode Most frequent value occurring in your data (frequency) Unaffected by extreme scores (outliers) Not useful when there are several values that occur equally often in a set. However can be more than one mode Can be measured on any level

Measures of Central Tendency 2. Median The values that falls exactly in the midpoint of a ranked distribution (50th percentile) Unaffected by extreme scores (outliers) 3. Mean (Arithmetic average) Average score Preferred measure; Most commonly reported measure Only for continuous variables (ratio, interval) Easily distorted by extreme values (outliers)

Standard deviation Most commonly used measure of dispersion around a mean how “spread out” are the values? Always reported with the mean – otherwise considered to be biased Can’t be done with nominal variables

Socio-behavioral model Table 1: Demographics of Elders with MR/SA Socio-behavioral model Variable MR/SA (N=350) NoMR/SA (N=48,014) Test Predisposing Characteristics Gender (male) 238 (68%) 25,064 (52%) OR=1.9*** Mean age (SD) 70 (5) 73 (7) t=4.5* Race (white) 260 (74%) 28,741 (59%) (SSI/SSDI) 199 (57%) 29,131 (61%) NS Enabling resources Dually eligible 303 (87%) 43,226 (90%) OR=0.7* FFS coverage 262 (75%) 34,283 (71%) Low state SA coverage 141 (40%) 16,899 (35%) OR= OR= 1.2* Urban location 213 (61%) 30,027 (63%) Need factors SMI diagnosis 151 (43%) 7,540 (16%) OR= 4.1*** Long-term SA diagnosis 19 (5%) 5,549 (12%) OR= 0.4*** ***p<.001 *p<.05

Bimodal Example Diagnostic Category Anxiety disorders Eating disorders Mood disorders Personality disorders Psychotic disorders Number of Clients (Frequency) 8 4 3 5

Measures of Dispersion

Dispersion Definition- Measures the dispersion of responses of a given variable. i.e. Age Types Range Standard deviation

The Range Easiest measure to calculate and simplest to understand Weakest measure Influenced by outliers (extreme measures) in your data set Example- Age range of adolescent girls in outpatient treatment for Oxycontin at Victory Programs. Range= 13-18 years of age.

Standard Deviation (SD) Most commonly used measure of dispersion around a mean how “spread out” are the values. Tells us how far the average scores varies from the mean Measured at the interval or ratio level and sometimes the ordinal level The smaller the SD, the more the scores cluster around the mean. The larger the SD, the more the scores are spread or dispersed away from the mean. Never a negative value. Goal+ small SD as it will be a more representative of the mean (average) of the data

Demographics Table

Text Supporting Previous Table

Buzi et al. (2007) Reading What is the study rational? What is the mean age of the participants? Range? What scale was used to measure depression? What is the reliability of this scale? What is the frequency of individuals who reported having at least one drink of alcohol in the past 30 days?

Narrative Example

Qualitative Example- Demographics

Choosing Measures of Central Tendency- Variable Types Measures Mean Median Mode Best Uses Interval or ratio data Ordinal, interval, or ratio data Nominal, ordinal, interval, or ratio data