Project measure / variable:   Brown2   probe_corr_ent

ID, description, units MPD:22519   probe_corr_ent   probe trial correct quadrant total entries   [n]  
Data set, strains Brown2   inbred   13 strains     sex: both     age: 10-18wks
Procedure Barnes circular maze
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  STRAIN COMPARISON PLOT
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Brown2 - probe trial correct quadrant total entries



  MEASURE SUMMARY
Measure Summary FemaleMale
Number of strains tested13 strains13 strains
Mean of the strain means8.44   n 9.04   n
Median of the strain means8.00   n 8.75   n
SD of the strain means± 3.30 ± 3.31
Coefficient of variation (CV)0.390 0.366
Min–max range of strain means2.92   –   17.1   n 4.45   –   14.8   n
Mean sample size per strain11.0   mice 10.6   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
sex 1 4.3819 4.3819 0.2579 0.612
strain 12 2617.0932 218.0911 12.8366 < 0.0001
sex:strain 12 315.0886 26.2574 1.5455 0.1082
Residuals 259 4400.3697 16.9898


Q-Q normality assessment based on residuals

  


  STRAIN MEANS (UNADJUSTED)
  
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Strain Sex Mean SD N mice SEM CV Min, Max Z score
129S1/SvImJ f 10.6 4.01   12 1.16 0.379 3.0, 16.0 0.66
129S1/SvImJ m 9.83 5.34   12 1.54 0.543 1.0, 21.0 0.24
A/J f 2.92 2.47   12 0.712 0.846 -1.68
A/J m 4.67 3.87   18 0.911 0.828 -1.32
AKR/J f 7.58 3.0   12 0.866 0.395 3.0, 12.0 -0.26
AKR/J m 6.67 2.93   12 0.847 0.44 3.0, 12.0 -0.72
BALB/cByJ f 6.19 2.69   21 0.588 0.435 -0.68
BALB/cByJ m 8.75 4.0   12 1.16 0.457 3.0, 16.0 -0.09
BALB/cJ f 10.9 5.3   14 1.42 0.485 4.0, 22.0 0.75
BALB/cJ m 11.4 5.17   10 1.63 0.453 3.0, 19.0 0.71
C3H/HeJ f 9.1 4.23   10 1.34 0.465 4.0, 16.0 0.2
C3H/HeJ m 7.6 3.95   10 1.25 0.52 -0.44
C57BL/6J f 8.0 5.64   11 1.7 0.705 2.0, 18.0 -0.13
C57BL/6J m 7.0 3.74   12 1.08 0.535 1.0, 12.0 -0.62
CAST/EiJ f 8.33 5.03   3 2.91 0.604 3.0, 13.0 -0.03
CAST/EiJ m 14.4 3.36   5 1.5 0.233 10.0, 19.0 1.62
DBA/2J f 7.33 2.35   12 0.678 0.32 3.0, 12.0 -0.34
DBA/2J m 11.0 3.38   11 1.02 0.307 5.0, 16.0 0.59
FVB/NJ f 17.1 6.74   11 2.03 0.395 9.0, 31.0 2.63
FVB/NJ m 14.8 5.75   12 1.66 0.388 5.0, 26.0 1.74
MOLF/EiJ f 6.17 4.41   12 1.27 0.715 1.0, 15.0 -0.69
MOLF/EiJ m 4.45 3.7   11 1.11 0.83 -1.39
SJL/J f 8.17 2.95   12 0.851 0.361 4.0, 13.0 -0.08
SJL/J m 6.67 2.45   9 0.816 0.367 4.0, 11.0 -0.72
SM/J f 7.33 3.51   3 2.03 0.479 4.0, 11.0 -0.34
SM/J m 10.3 4.18   6 1.71 0.404 7.0, 17.0 0.38


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ f 10.5833 1.1899 12.9264 8.2403
129S1/SvImJ m 9.8333 1.1899 12.1764 7.4903
A/J f 2.9167 1.1899 5.2597 0.5736
A/J m 4.6667 0.9715 6.5798 2.7536
AKR/J f 7.5833 1.1899 9.9264 5.2403
AKR/J m 6.6667 1.1899 9.0097 4.3236
BALB/cByJ f 6.1905 0.8995 7.9617 4.4193
BALB/cByJ m 8.75 1.1899 11.0931 6.4069
BALB/cJ f 10.9286 1.1016 13.0978 8.7593
BALB/cJ m 11.4 1.3035 13.9667 8.8333
C3H/HeJ f 9.1 1.3035 11.6667 6.5333
C3H/HeJ m 7.6 1.3035 10.1667 5.0333
C57BL/6J f 8.0 1.2428 10.4473 5.5527
C57BL/6J m 7.0 1.1899 9.3431 4.6569
CAST/EiJ f 8.3333 2.3798 13.0195 3.6472
CAST/EiJ m 14.4 1.8434 18.0299 10.7701
DBA/2J f 7.3333 1.1899 9.6764 4.9903
DBA/2J m 11.0 1.2428 13.4473 8.5527
FVB/NJ f 17.0909 1.2428 19.5382 14.6436
FVB/NJ m 14.8333 1.1899 17.1764 12.4903
MOLF/EiJ f 6.1667 1.1899 8.5097 3.8236
MOLF/EiJ m 4.4545 1.2428 6.9018 2.0073
SJL/J f 8.1667 1.1899 10.5097 5.8236
SJL/J m 6.6667 1.374 9.3722 3.9611
SM/J f 7.3333 2.3798 12.0195 2.6472
SM/J m 10.3333 1.6827 13.6469 7.0197


  LEAST SQUARES MEANS (MODEL-ADJUSTED), SEXES COMBINED
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ both 10.2083 0.8414 11.8651 8.5515
A/J both 3.7917 0.7681 5.3041 2.2792
AKR/J both 7.125 0.8414 8.7818 5.4682
BALB/cByJ both 7.4702 0.7458 8.9388 6.0016
BALB/cJ both 11.1643 0.8533 12.8446 9.484
C3H/HeJ both 8.35 0.9217 10.1649 6.5351
C57BL/6J both 7.5 0.8603 9.194 5.806
CAST/EiJ both 11.3667 1.5051 14.3304 8.4029
DBA/2J both 9.1667 0.8603 10.8607 7.4726
FVB/NJ both 15.9621 0.8603 17.6562 14.2681
MOLF/EiJ both 5.3106 0.8603 7.0046 3.6166
SJL/J both 7.4167 0.9088 9.2062 5.6271
SM/J both 8.8333 1.4573 11.703 5.9637




  GWAS USING LINEAR MIXED MODELS