STATA Flashcards
Learn definitions and formulas!
Systematic measurement error
“Mismeasurement bias”, it produces a systematic mismeasurement of the intended characteristics.
Random Measurement Error
It introduces chaotic distortion in the measurement process
Reliable Measure
A measure free of random measurement errors. A measure that is a consistent measure of the concept.
Valid Measure
A measure that records the TRUE VALUE of the intended concept. It does not measure any UNINTENDED characteristics. It is free of any SYSTEMATIC measurement error.
Over-time consistency
To assess RELIABILITY. * TEST RE-TEST METHOD, repeating the same test hoping to get the same results. *ALTERNATIVE FORM METHOD, the test is administered again in a roughly equivalent form.
Internal Consistency
Assessing reliabikity. * SPLIT-HALF METHOD: half of the questions are administered to a group, half to another. *CRONBACH’S ALPHA: statistical measure of internal consistency.
Assessing Validity
*FACE VALIDITY: informed judgement is used to determine whether a measurement strategy is measuring what it should. *CONTSTRUCT VALIDITY: assessment of an association between the measured concept with other concepts as we would expect it to be.
The question to address for “Validity”
Are we aiming at the correct target?
The question to address for Reliability
How close have we got to the target?
Variable
The result of the measurement process. The empirical measurement of a concept. Each question in a survey gives birth to a variable. A variable has a name, and at least two values. Nominal, Ordinal, Internal Level Variables. (Dummies)
What are Nominal and Ordinal variables also referred to as?
Categorical variables
Nominal Variables
They take on values that are not numbers and cannot be ranked.
Ordinal Variables
They take on values that are not numbers, but there is a criterion allowing us to RANK them. Ordinal variables communicate the RELATIVE AMOUNT of the characteristic being measured.
Interval Level Variables
They take on numerical values, providing the most precise measurement of the amount of an observed characteristic.
Decision Tree for Variable Types
Are the values numerical? Yes (Interval level variable), No —> Can we rank the values? Yes (Ordinal), No(Nominal)
Data file
.dta, this is the dataset with all its information. No analysis or results are recorded.
Do file
.do, analysis. It records commands only. It is a file that runs all the commands that you do for your analysis.
Log file
.smcl, RESULTS. It records commands and results of your analysis.
describe varname
n°observations, n°var, size, date of creation. For each variable it provides a description in term kf storage type, format and variable label.
codebook varname
information on each variable: type, RANGE, number of MISSINGS, value LABELS and counts for each value
Creating value labels: eg. Likert
label define likert 1 “Strongly Agree” 2 “Agree” … … 5 “Strongly Disagree” ******* label values var_1 var_2 var_3 likert
First step of creating value labels
label define label_nane numeric_code1 “label1” numeric_code2 “label2”
Second step of creating value labels
label values var_1 var_2 .. label_name
Missing values coding, es. gov_int, 6
mvdecode gov_int, mv(6=.)