**AFNI Notes: 10/11/2019**

**Good AFNI summary (pdf)**

Test | Description | Comment |

3dttest++ | a relatively flexible voxel based t-test | really good option for obvious contrasts |

3dttest | as above without new features | largely decommissioned |

3dMEMA | like 3dttest++ but uses t-stat for scaling | needs REML, conceptually cool, not sure of benefit |

3dMannWhitney | non parametric 2 group ttest non-paired | maybe if the data is just that noisy |

3dKruskalWallis | as above for >2 groups | or multiple noisy datasets |

3dWilcoxon | paired 2 group non parametric | etc. |

3dFriedman | as above for >2 groups | etc. |

3dLME | a nice general LM frame work | good option for interactions etc. |

3dMVM | like 3dLME with a few less bells | if your comfortable with LME just stay with that |

3dANOVAx | Does x way ANOVAs | as it needs equal groups and other reasons don't use |

3dRegAna | Does multiple regression | as it does calculations in short and other reasons don't use |

**3dttest++**Student T test with 1 or 2 sets of data (labeled 'A' and 'B').

-prefix p p = output

-mask mmm mmm = specified mask.

-setA/-setB Use this to specify group membership

1 group just give setA to contrast with base 0 [or setB versus -singletonA 10/perfect10+tlrc'[1]']

2 group will give setA-setB, setA(v. null), and setB(v. null) [-BminusA flips contrast]

Short form: -labelA Group1 -setA mydatasub1+tlrc'[1]' mydatasub2+tlrc'[1]' … etc.

Long form: -setA Group1 sub1 mydatasub1+tlrc'[1]' sub2 mydatasub2+tlrc'[1]' … etc.

-covariates COVAR_FILE a text file with a table for numeric covariate(s)[columns] for each subj[rows]

Rows must match dataset label example:

subject IQ age GMfrac

Elvis 143 42 Elvis_GM+tlrc[8]

Fred 85 59 Fred_GM+tlrc[8]

Ethel 109 49 Ethel_GM+tlrc[8]

Lucy 133 32 Lucy_GM+tlrc[8]

Ricky 121 37 Ricky_GM+tlrc[8]

can only be used with the short form '-setX' option if each input dataset has only 1 sub-brick

-center NONE/DIFF/SAME do you remove mean of covariates? Group or set mean? [default DIFF]

-paired is the data paired. If paired setA will be ignored

-pooled/unpooled for un/pooled variance (blocks covariates)

-toz Convert output t-statistics to z-scores

-rankize Convert the data (and covariates, if any)

-brickwise run ttest on each subbrick for each brick provided

-resid q q = Output residuals to look at with 3dFWHMx

-randomsign makes better residuals by flipping directionality

-clustsim will run 10000 iteration clustsim and apply results to file

-Clustsim keep .1D files

-center NONE/DIFF/SAME do you remove mean of covariates? Group or set mean? [default DIFF]

-paired is the data paired. If paired setA will be ignored

-pooled/unpooled for un/pooled variance (blocks covariates)

-toz Convert output t-statistics to z-scores

-rankize Convert the data (and covariates, if any)

-brickwise run ttest on each subbrick for each brick provided

-resid q q = Output residuals to look at with 3dFWHMx

-randomsign makes better residuals by flipping directionality

-clustsim will run 10000 iteration clustsim and apply results to file

-Clustsim keep .1D files

-CLUSTSIM keep all temp files

-ETAC Equitable Thresholding And Clustering

-prefix_clustsim cc cc = prefix of clustsimfiles

## Understanding ClustSim:

Permutations

## Understanding ETAC: Article

Parameter tuning:

**3dLME ** Multivariate Linear Model

-jobs NJOBS processors

-prefix Output file

-mask MASK Process voxels inside this mask only.** -model FORMULA** Test of model like '~A*B+C+A:B" + = factors; : = interaction * = both (A*B = A+B+A:B)

-SS_type NUMBER Specify the type for sums of squares: 1=sequential 3=marginal

-qVars variable_list comma separated list of quantitative variables

-qVarCenters VALUES comma separated list of means of quantitative variables [default = group mean]

-vVars variable single voxel-wise covariate, i.e. subXTime1+tlrc column in dataTable

-vVarCenters VALUE centering values for voxel-wise covariates [default=mean of all subjects]

-ranEff FORMULA Specify the random effects. For just Subjects = "~1" but could be"~1+RT"

-num_glf/num_glt NG number of general linear F-tests/t-tests

-glfCode/gltCode k CODING Specify the k-th general linear F-test/t-test

Coding example: 'Condition : 1*A -1*B & 1*A -1*C Emotion : 1:pos'

- Weights don't need to sum to 0
- If covariate is not given the mean is used
- If a categorical is not given the mean of all levels I used

-glfLabel/gltLabel k label Specify the label for the k-th GLF/GLT** -dataTable** List the data structure with a header as the first line.

- Last item command
- Header on first line must start with Subj and end with InputFile
- Can be a file '-dataTable @table.txt'

-corStr FORMULA Correlation structure of the residuals (like AR or ARMA) if timeseries entered.

-cutoff threshold: Specify the cutoff value to obtain voxel-wise accuracy [default is 0]

-ICC intra-class correlation [for variables in -ranEff]

-LOGIT Do logistic regression [no random effects]