SPSS - Health Study Research Project Topic: Link Between The Low Carbohydrate Diet and Cardiovascular Disease
Intro to SPSS
General tips and hints about using SPSS and opening up files into SPSS
https://www.youtube.com/watch?v=ADDR3_Ng5CA
SPSS Tutorial on Frequencies
Descriptive statistics for continuous variables (age, income, BMI)
https://www.youtube.com/watch?v=zI8tE81IeSk&list=UUXLbK1bH-w1oklGm4dLYrHw
SPSS Tutorial on Descriptive Statistics
Descriptive statistics for other variables like dichotomous and categorical variables (education, gender, marital status, race, etc.)
https://www.youtube.com/watch?v=c4mGKguUnvc&list=UUXLbK1bH-w1oklGm4dLYrHw
One-Sample t-Test
Comparing one continuous variable with a population mean (etc. is the study population’s BMI different than the population BMI; is the study populations mean age different than the mean age of the general population, etc.)
https://www.youtube.com/watch?v=jTJdj7ZYmmU&list=UUXLbK1bH-w1oklGm4dLYrHw
Paired-Sample t-Tests
Comparing one continuous variable in either two matched samples (blood pressure of participants on new drug versus placebo, matched on age, gender, and race), or in the same sample at two time points (e.g. SAT scores before and after an SAT prep class; BMI before and after a weight-loss intervention, blood pressure before and after meditation)
https://www.youtube.com/watch?v=eanXmHlW5qE&list=UUXLbK1bH-w1oklGm4dLYrHw
Two Independent Sample t-Tests
Comparing a continuous variable in two different populations, not matched on any variables: mean age of breast cancer diagnosis in Hispanic versus African-American population; # colds in a year in prechool aged children versus school-aged children; height of children on steroids versus those never had steroids
https://www.youtube.com/watch?v=qOH46VVm1Uo&list=UUXLbK1bH-w1oklGm4dLYrHw
Correlations
How do two continuous variables relate to one another? As one variable increases, does the other variable decrease, stay the same, or increase? E.g correlation of age and income is generally relatively high and linear – as one gets older, one increases in income
https://www.youtube.com/watch?v=cNrnSEWKJgg&list=UUXLbK1bH-w1oklGm4dLYrHw
Chi-Square
Comparison of a dichotomous or categorical outcome across two or more independent groups: e.g. are there more women with cervical cancer among Caucasian, African-American, Hispanic, Asian-American, Native American, or other racial groups? Comparison of cancer status across racial groups, or across education groups, or across income levels; comparison of BMI across different job types or levels of employment (salaried, hourly, contractor, commission-based, etc.) or different shifts (day-shift, night-shift, varied).
https://www.youtube.com/watch?v=Ahs8jS5mJKk
Analysis of Variance (ANOVA) and F-Test
Comparison of a continuous outcome across more than two groups: e.g. BMI comparison of low fat, low calories, low carb, and control groups; blood pressure comparison across those on clinical trial drug A, clinical trial drug B, and a control group.
https://www.youtube.com/watch?v=C3-a5jrCjhk
Linear Regression
Continuous variable outcome with any number of risk factors in a regression model; using risk factors, can we model a prediction of the continuous variable
E.g. knowing the risk factors of age, gender, race, income, education, BMI, family history, and other health history, can we predict fasting blood glucose levels?
Fasting blood glucose level here is the continuous outcome.
https://www.youtube.com/watch?v=JVwEdhEiGJg
Logistic Regression
Dichotomous variable outcome with any number of risk factors in a regression model; using risk factors, can we model a prediction of the continuous variable
E..g. knowing the risk factors of age, gender, race, income, education, BMI, family history, and other health history, can we predict diabetes status?
Diabetes status here is the dichotomous variable (diabetes or no diabetes)
https://www.youtube.com/watch?v=ODyRncSMMo4
Logistic Regression, Part II
https://www.youtube.com/watch?v=ILEdg0UTTXQ&list=UU3j4fRCt2VGsttiPs9DXWMQ