User:Leonchoi

ANTH174-10 678. Food Stress or Hunger

    48    . = Missing data
    47    1 = food constant
    62    2 = occasional hunger or famine
    26    3 = periodic or chronic hunger
     3    4 = starvation or evidence of protein deficiency
                  (note: exact coding distinction between 3 and 4 unclear)

Day One Class Notes

To create a link, surround the hyperlink with double brackets. Copy the variable codes in a previously made program and insert your own variable to start your project

hashmarks # or ## or ### are used as a way to signal the program to not code the line

double equal sign (==) surrounding Text creates a header.

Ctrl+A copies all text in page

Day 2 Class Notes

1. Choose carefully, look at codebook and literature first: Sources for codes on the SCCS - find the literature where authors have contributed SCCS codes, and the literature where authors study those codes to get research findings. Copy to your project word-file the codebook number, and the full description of the variable from the codebook.
2. Then see if your variable number is found in this program: ---EduMod-52 speedy program or ---EduMod-52 working program|---. If it is, then place a # (comment out this line) IN FRONT of your variable. DO THIS FOR ANY VARIABLE THAT SEEMS EQUIVALENT, e.g., ### pctFemPolyg=SCCS$v872. If you dont do this they you will get a VIF error that says that a variable was aliased. To see the errors, move the cursor bar up to the FIRST error in the program, and ignore any later errors. Report that error to me if you cant solve the problem.

Day 3 Class Notes

Imputing Data for Regression Analysis http://intersci.ss.uci.edu/wiki/index.php/Imputing_data_for_Regression_Analysis

MAIN PAGE (easier) http://intersci.ss.uci.edu/wiki/index.php/Human_Social_Complexity_-_World_Cultures_2010

Day 4 Class Notes

Reminder: sign up for Friday's conference at the third floor of Anteater Instructional Bldg at room 3030 @ 1:30pm-3:00pm...getting easy extra units (and enjoying the process) is always a good idea! Class Code 71500

Solving Galton's problem of nonindependence using 2-stage least squares to improve regression analysis that set the stage for Bayesian causal analysis.

   * detecting causality i.e. low p-value from the acquired data
   * imputing missing data; Donald Ruben predicts missing values for different configurations thorough taking best described dependent variables settings like climate(called auxiliary data base)and uses probability to create these values. Theses predictions build unique data sets, which in turn can be combined to create one complete set.
   * instrumental variables are used to correct concentrated, patterned errors, which should not occur in a data set. Essentially takes observations to create an experiment and plays a roll in identifying and estimating causal effects.
   * 2-stage least squares (2SLS0: instrumental variables in 2SLS reduce the significance by clustering the effective sample size into groups. Weighted matrices and matrix multiplication are used as the physical process to find the prediction. 

Detecting Causality with Bayesian Causal graphs

   * independent var X has a weighted correlation to depvar Y which can be graphed.
   * Multiple imputed (MI) missing data are taken into account by instrumental variables and auxiliary data base. 

Day 5 Class Notes

Choosing a new dependent variable from the codebook:

1. Run your ==1A| xUR<-
2. Results: ==2B| xUR< from last time note <--keep
3. Run your ==3A| xR<-
4. Copy:- to =4B| your results using Textpad
5. Copy ==1A| to ==5A| and CHANGE depvar<--SCCS$v860 to YOUR depvar<--SCCS$XXXX
6. Also CHANGE depvarname<--"polygyny" to depvarname<--"Your depvar name"
7. check 2SLS checklist for consistency in naming
8. Run your ==5A| xUR<-
9. Copy:- to =6B| (you create this header) your results using Textpad, then markup significant results with <--keep
10. Write down those vars to <--keep
11. Copy ==6A| to ==8A| and change the header
12. use Ctrl-Find to search in ==8A| for "xR<-" and erase all but the fyll, fydd, and variables to <--keep (YOUR RESTRICTED MODEL)

Day 6 Class Notes

2SLS Checklist: [ ] Login -- write into your User:page - edit "Talk" page for the class and add your user page within square brackets [ ] Choose an EduMod-XX site - add your user page within square brackets [ ] Instructions at EduMod-54: Imputation and Regression - RECOPY xR Restricted model contents to your EduMod-XX site [ ] EduMod-66: Imputation and Regression‎ [ ] ‎Programs: open R [ ] Copy YOUR new ==A| program ...== to R, if you get results then copy results [ ] ‎From "Programs": open TextPad, add space, paste results [ ] Ctrl-A in TextPad to copy [ ] Make a new window at bottom of your EduMod page ==B|...== , paste into this page (your Textpad results) [ ]1 Now choose a new dependent variable from the codebook, change your copy of the program accordingly [ ]2 Run your edited R program, see if you have results, think about whether to keep or change [ ]3 When your variable is chosen, check Sources for codes on the SCCS online readings for the topic of your study [ ]4 Add those references to your PAPER and you Ueser:Name... page. Find the variables those authors used. [ ]5 Prepare a powerpoint with your results if you have R2 > .20 [ ]6 If not, add a few independent variables from your readings, OR CHANGE YOUR DEPENDENT VARIABLE, Repeat from 1 above

Day 7 Class Notes

Write down important variable to run again:

money 0.097 2.705 515.768 0.101 2.282 <-- keep

plunder -0.259 2.432 1623.896 0.119 1.739 <-- keep

hunt 0.140 2.933 787.369 0.087 5.689 <-- keep

foodscarc 0.192 9.930 44.591 0.003 1.445 <-- keep

himilexp -0.314 3.622 1239.033 0.057 1.794 <-- keep

678: food stress

1265: famine

Map of v678 Famine

http://edumodgis.ss.uci.edu/SCCS1/default.aspx

678. Food Stress or Hunger

    48    . = Missing data
    47    1 = food constant
    62    2 = occasional hunger or famine
    26    3 = periodic or chronic hunger
     3    4 = starvation or evidence of protein deficiency
     (note: exact coding distinction between 3 and 4 unclear)

Map Level 1

Map Level 2